sites to use for research paper

Explore millions of high-quality primary sources and images from around the world, including artworks, maps, photographs, and more.

Explore migration issues through a variety of media types

• Part of The Streets are Talking: Public Forms of Creative Expression from Around the World
• Part of The Journal of Economic Perspectives, Vol. 34, No. 1 (Winter 2020)
• Part of Cato Institute (Aug. 3, 2021)
• Part of University of California Press
• Part of Open: Smithsonian National Museum of African American History & Culture
• Part of Indiana Journal of Global Legal Studies, Vol. 19, No. 1 (Winter 2012)
• Part of R Street Institute (Nov. 1, 2020)
• Part of Leuven University Press
• Part of UN Secretary-General Papers: Ban Ki-moon (2007-2016)
• Part of Perspectives on Terrorism, Vol. 12, No. 4 (August 2018)
• Part of Leveraging Lives: Serbia and Illegal Tunisian Migration to Europe, Carnegie Endowment for International Peace (Mar. 1, 2023)
• Part of UCL Press

Harness the power of visual materials—explore more than 3 million images now on JSTOR.

Enhance your scholarly research with underground newspapers, magazines, and journals.

Explore collections in the arts, sciences, and literature from the world’s leading museums, archives, and scholars.

A free, AI-powered research tool for scientific literature

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Introducing semantic reader in beta.

Stay Connected With Semantic Scholar Sign Up What Is Semantic Scholar? Semantic Scholar is a free, AI-powered research tool for scientific literature, based at the Allen Institute for AI.

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Reference management. Clean and simple.

The top list of academic research databases

2. Web of Science

5. ieee xplore, 6. sciencedirect, 7. directory of open access journals (doaj), get the most out of your academic research database, frequently asked questions about academic research databases, related articles.

Whether you are writing a thesis , dissertation, or research paper it is a key task to survey prior literature and research findings. More likely than not, you will be looking for trusted resources, most likely peer-reviewed research articles.

Academic research databases make it easy to locate the literature you are looking for. We have compiled the top list of trusted academic resources to help you get started with your research:

Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Besides searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator .

• Coverage: 90.6 million core records
• References: N/A
• Discipline: Multidisciplinary
• Access options: Limited free preview, full access by institutional subscription only
• Provider: Elsevier

Web of Science also known as Web of Knowledge is the second big bibliographic database. Usually, academic institutions provide either access to Web of Science or Scopus on their campus network for free.

• Coverage: approx. 100 million items
• References: 1.4 billion
• Access options: institutional subscription only
• Provider: Clarivate (formerly Thomson Reuters)

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC) .

• Coverage: approx. 35 million items
• Discipline: Medicine and Biological Sciences
• Access options: free
• Provider: NIH

For education sciences, ERIC is the number one destination. ERIC stands for Education Resources Information Center, and is a database that specifically hosts education-related literature.

• Coverage: approx. 1.6 million items
• Discipline: Education
• Provider: U.S. Department of Education

IEEE Xplore is the leading academic database in the field of engineering and computer science. It's not only journal articles, but also conference papers, standards and books that can be search for.

• Coverage: approx. 6 million items
• Discipline: Engineering
• Provider: IEEE (Institute of Electrical and Electronics Engineers)

ScienceDirect is the gateway to the millions of academic articles published by Elsevier, 1.4 million of which are open access. Journals and books can be searched via a single interface.

• Coverage: approx. 19.5 million items

The DOAJ is an open-access academic database that can be accessed and searched for free.

• Coverage: over 8 million records
• Provider: DOAJ

JSTOR is another great resource to find research papers. Any article published before 1924 in the United States is available for free and JSTOR also offers scholarships for independent researchers.

• Coverage: more than 12 million items
• Provider: ITHAKA

Start using a reference manager like Paperpile to save, organize, and cite your references. Paperpile integrates with PubMed and many popular databases, so you can save references and PDFs directly to your library using the Paperpile buttons:

Scopus is one of the two big commercial, bibliographic databases that cover scholarly literature from almost any discipline. Beside searching for research articles, Scopus also provides academic journal rankings, author profiles, and an h-index calculator .

PubMed is the number one resource for anyone looking for literature in medicine or biological sciences. PubMed stores abstracts and bibliographic details of more than 30 million papers and provides full text links to the publisher sites or links to the free PDF on PubMed Central (PMC)

28 Best Academic Search Engines That make your research easier

This post may contain affiliate links that allow us to earn a commission at no expense to you. Learn more

If you’re a researcher or scholar, you know that conducting effective online research is a critical part of your job. And if you’re like most people, you’re always on the lookout for new and better ways to do it. 

I’m sure you are familiar with some research databases. But, top researchers keep an open mind and are always looking for inspiration in unexpected places. 

This article aims to give you an edge over researchers that rely mainly on Google for their entire research process.

Our list of 28 academic search engines will start with the more familiar to less.

Table of Contents

#1. Google Scholar

Google Scholar is an academic search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines.

Great for academic research, you can use Google Scholar to find articles from academic journals, conference proceedings, theses, and dissertations. The results returned by Google Scholar are typically more relevant and reliable than those from regular search engines like Google.

Tip: You can restrict your results to peer-reviewed articles only by clicking on the “Scholarly”

• Scholarly results are typically more relevant and reliable than those from regular search engines like Google.
• You can restrict your results to peer-reviewed articles only by clicking on the “Scholarly” tab.
• Google Scholar database Coverage is extensive, with approx. 200 million articles indexed.
• Abstracts are available for most articles.
• Related articles are shown, as well as the number of times an article has been cited.
• Links to full text are available for many articles.
• Abstracts are only a snippet of the full article, so you might need to do additional searching to get the full information you need.
• Not all articles are available in full text.

Google Scholar is completely free.

#2. ERIC (Education Resources Information Center) 

ERIC (short for educational resources information center) is a great academic search engine that focuses on education-related literature. It is sponsored by the U.S. Department of Education and produced by the Institute of Education Sciences. 

ERIC indexes over a million articles, reports, conference papers, and other resources on all aspects of education from early childhood to higher education. So, search results are more relevant to Education on ERIC. 

• Extensive coverage: ERIC indexes over a million articles, reports, and other resources on all aspects of education from early childhood to higher education.
• You can limit your results to peer-reviewed journals by clicking on the “Peer-Reviewed” tab.
• Great search engine for educators, as abstracts are available for most articles.

ERIC is a free online database of education-related literature. 

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#3. Wolfram Alpha

Wolfram Alpha is a “computational knowledge engine” that can answer factual questions posed in natural language. It can be a useful search tool. 

Type in a question like “What is the square root of 64?” or “What is the boiling point of water?” and Wolfram Alpha will give you an answer.

Wolfram Alpha can also be used to find academic articles. Just type in your keywords and Wolfram Alpha will generate a list of academic articles that match your query.

Tip: You can restrict your results to peer-reviewed journals by clicking on the “Scholarly” tab.

• Can answer factual questions posed in natural language.
• Can be used to find academic articles.
• Results are ranked by relevance.
• Results can be overwhelming, so it’s important to narrow down your search criteria as much as possible.
• The experience feels a bit more structured but it could also be a bit restrictive

Wolfram Alpha offers a few pricing options, including a “Pro” subscription that gives you access to additional features, such as the ability to create custom reports. You can also purchase individual articles or download them for offline use.

Pro costs $5.49 and Pro Premium costs $9.99

#4. iSEEK Education 

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iSEEK is a search engine targeting students, teachers, administrators, and caregiver. It’s designed to be safe with editor-reviewed content.

iSEEK Education also includes a “Cited by” feature which shows you how often an article has been cited by other researchers.

• Editor-reviewed content.
• “Cited by” feature shows how often an article has been cited by other researchers.
• Limited to academic content.
• Doesn’t have the breadth of coverage that some of the other academic search engines have.

iSEEK Education is free to use.

#5. BASE (Bielefeld Academic Search Engine)

BASE is hosted at Bielefeld University in Germany and that’s where it name stems from (Bielefeld Academic Search Engine). 

Known as “one of the most comprehensive academic web search engines,” it contains over 100 million documents from 4,000 different sources. 

Users can narrow their search using the advanced search option, so regardless of whether you need a book, a review, a lecture, a video or a thesis, BASE has what you need.

BASE indexes academic articles from a variety of disciplines, including the arts, humanities, social sciences, and natural sciences.

• One of the world’s most voluminous search engines, 
• Indexes academic articles from a variety of disciplines, especially for academic web resources
• Includes an “Advanced Search” feature that lets you restrict your results to peer-reviewed journals.
• Doesn’t include abstracts for most articles.
• Doesn’t have related articles, references, cited by

BASE is free to use.

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CORE is an academic search engine that focuses on open access research papers. A link to the full text PDF or complete text web page is supplied for each search result. It’s academic search engine dedicated to open access research papers.

• Focused on open access research papers.
• Links to full text PDF or complete text web page are supplied for each search result.
• Export formats include BibTeX, Endnote, RefWorks, Zotero.
• Coverage is limited to open access research papers.
• No abstracts are available for most articles.
• No related articles, references, or cited by features.

CORE is free to use.

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#7. Science.gov

Science.gov is a search engine developed and managed by the United States government. It includes results from a variety of scientific databases, including NASA, EPA, USGS, and NIST. 

US students are more likely to have early exposure to this tool for scholarly research. 

• Coverage from a variety of scientific databases (200 million articles and reports).
• Links to full text are available for some articles.

Science.gov is free to use.

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#8. Semantic Scholar

Semantic Scholar is a recent entrant to the field. Its goal is to provide more relevant and effective search results via artificial intelligence-powered methods that detect hidden relationships and connections between research topics.

• Powered by artificial intelligence, which enhances search results.
• Covers a large number of academic articles (approx. 40 million).
• Related articles, references, and cited by features are all included.
• Links to full text are available for most articles.

Semantic Scholar is free to use.

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#9. RefSeek

RefSeek searches more than five billion documents, including web pages, books, encyclopedias, journals, and newspapers.

This is one of the free search engines that feels like Yahoo with a massive directory. It could be good when you are just looking for research ideas from unexpected angles. It could lead you to some other database that you might not know such as the CIA The World Factbook, which is a great reference tool.

• Searches more than five billion documents.
• The Documents tab is very focused on research papers and easy to use.
• Results can be filtered by date, type of document, and language.
• Good source for free academic articles, open access journals, and technical reports.
• The navigation and user experience is very dated even to millenials…
• It requires more than 3 clicks to dig up interesting references (which is how it could lead to you something beyond the 1st page of Google)
• The top part of the results are ALL ads (well… it’s free to use)

RefSeek is free to use.

#10. ResearchGate 

A mixture of social networking site + forum + content databases where researchers can build their profile, share research papers, and interact with one another.

Although it is not an academic search engine that goes outside of its site, ResearchGate ‘s library of works offers an excellent choice for any curious scholar.

There are more than 100 million publications available on the site from over 11 million researchers. It is possible to search by publication, data, and author, as well as to ask the researchers questions. 

• A great place to find research papers and researchers.
• Can follow other researchers and get updates when they share new papers or make changes to their profile.
• The network effect can be helpful in finding people who have expertise in a particular topic.
• Interface is not as user friendly
• Can be overwhelming when trying to find relevant papers.
• Some papers are behind a paywall.

ResearchGate is free to use.

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#11. DataONE Search (formerly CiteULike) 

A social networking site for academics who want to share and discover academic articles and papers.

• A great place to find academic papers that have been shared by other academics.
• Some papers are behind a paywall

CiteULike is free to use.

#12. DataElixir 

DataElixir is deigned to help you find, understand and use data. It includes a curated list of the best open datasets, tools and resources for data science.

• Dedicated resource for finding open data sets, tools, and resources for data science.
• The website is easy to navigate.
• The content is updated regularly
• The resources are grouped by category.
• Not all of the resources are applicable to academic research.
• Some of the content is outdated.

DataElixir is free to use.

#13. LazyScholar – browser extension

LazyScholar is a free browser plugin that helps you discover free academic full texts, metrics, and instant citation and sharing links. Lazy Scholar is created Colby Vorland, a postdoctoral fellow at Indiana University.

• It can integrate with your library to find full texts even when you’re off-campus.
• Saves your history and provides an interface to find it.
• A pre-formed citation is availlable in over 900 citation styles.
• Can recommend you topics and scans new PubMed listings to suggest new papers
• Results can be a bit hit or miss

LazyScholar is free to use.

#14. CiteseerX – digital library from PenState

CiteseerX is a digital library stores and indexes research articles in Computer Science and related fields. The site has a robust search engine that allows you to filter results by date, author.

• Searches a large number of academic papers.
• Results can be filtered by date, author, and topic.
• The website is easy to use.
• You can create an account and save your searches for future reference.

CiteseerX is free to use.

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#15. The Lens – patents search 

The Lens or the Patent Lens is an online patent and scholarly literature search facility, provided by Cambia, an Australia-based non-profit organization.

• Searches for a large number of academic papers.

The price range can be free for non-profit use to $5,000 for commercial enterprise.

#16. Fatcat – wiki for bibliographic catalog 

Fatcat is an open bibliographic catalog of written works. The scope of works is somewhat flexible, with a focus on published research outputs like journal articles, pre-prints, and conference proceedings. Records are collaboratively editable, versioned, available in bulk form, and include URL-agnostic file-level metadata.

• Open source and collaborative
• You can be part of the community that is very focused on its mission
• The archival file-level metadata (verified digests and long-term copies) is a great feature.
• Could prove to be another rabbit hole
• People either love or hate the text-only interface

#17. Lexis Web – Legal database

Are you researching legal topics? You can turn to Lexis Web for any law-related questions you may have. The results are drawn from legal sites and can be filtered based on criteria such as news, blogs, government, and commercial. Additionally, users can filter results by jurisdiction, practice area, source and file format.

• Results are drawn from legal sites.
• Filters are available based on criteria such as news, blogs, government, and commercial.
• Users can filter results by jurisdiction, practice area, source and file format.
• Not all law-related questions will be answered by this search engine.
• Coverage is limited to legal sites only.

Lexis Web is free for up to three searches per day. After that, a subscription is required.

#18. Infotopia – part of the VLRC family

Infotopia touts itself as an “alternative to Google safe search.” Scholarly book results are curated by librarians, teachers, and other educational workers. Users can select from a range of topics such as art, health, and science and technology, and then see a list of resources pertaining to the topic. 

Consequently, if you aren’t able to find what you are looking for within Infotopia’s pages, you will probably find it on one of its many suggested websites.

#19. Virtual Learning Resources Center

Virtual Learning Resources Center (VLRC) is an academic search engine that features thousands of academic sites chosen by educators and librarians worldwide. Using an index generated from a research portal, university, and library internet subject guides, students and instructors can find current, authoritative information for school.

• Thousands of academic information websites indexed by it. You will also be able to get more refined results with custom Google search, which will speed up your research. 
• Many people consider VLRC as one of the best free search engines to start looking for research material. 
• TeachThought rated the Virtual LRC #3 in it’s list of 100 Search Engines For Academic Research
• More relevant to education 
• More relevant to students

Powered by Google Custom Search Engine (CSE), Jurn is a free online search engine for accessing and downloading free full-text scholarly papers. It was created by David Haden in a public open beta version in February 2009, initially for locating open access electronic journal articles in the arts and humanities.

After the indexing process was completed, a website containing additional public directories of web links to indexed publications was introduced in mid-2009. The Jurn search service and directory has been regularly modified and cleaned since then.

• A great resource for finding academic papers that are behind paywalls.
• The content is updated regularly.uren

Jurn is free to use.

#21. WorldWideScience

The Office of Scientific and Technical Information—a branch of the Office of Science within the U.S. Department of Energy—hosts the portal WorldWideScience , which has dubbed itself “The Global Science Gateway.”

Over 70 countries’ databases are used on the website. When a user enters a query, it contacts databases from all across the world and shows results in both English and translated journals and academic resources.

• Results can be filtered by language and type of resource
• Interface is easy to use
• Contains both academic journal articles and translated academic resources 
• The website can be difficult to navigate.

WorldWideScience is free to use.

#22. Google Books

A user can browse thousands of books on Google Books, from popular titles to old titles, to find pages that include their search terms. You can look through pages, read online reviews, and find out where to buy a hard copy once you find the book you are interested in.

#23. DOAJ (Directory of Open Access Journals)

DOAJ is a free search engine for scientific and scholarly materials. It is a searchable database with over 8,000 peer-reviewed research papers organized by subject. It’s one of the most comprehensive libraries of scientific and scholarly resources, with over 8,000 journals available on a variety of themes.

#24. Baidu Scholar

Baidu Xueshu (Academic) is the Chinese version for Google Scholar. IDU Scholar indexes academic papers from a variety of disciplines in both Chinese and English.

• Articles are available in full text PDF.
• Covers a variety of academic disciplines.
• No abstracts are available for most articles, but summaries are provided for some.
• A great portal that takes you to different specialized research platform
• You need to be able to read Chinese to use the site
• Since 2021 there is a rise of focus on China and the Chinese Communist Party

Baidu Scholar is free to use.

#25. PubMed Central

PubMed is a free search engine that provides references and abstracts for medical, life sciences, and biomedical topics.

If you’re studying anything related to healthcare or science, this site is perfect. PublicMed Central is operated by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine. It contains more than 3 million full-text journal articles. 

It’s similar to PubMed Health, which focuses on health-related research and includes abstracts and citations to over 26 million articles.

#26. MEDLINE®

MEDLINE® is a paid subscription database for life sciences and biomedicine that includes more than 28 million citations to journal articles. For finding reliable, carefully chosen health information, Medline Plus provides a powerful search tool and even a dictionary.

• A great database for life sciences and biomedicine.
• Contains more than 28 million references to journal articles.
• References can be filtered by date, type of document, and language.
• The database is expensive to access.
• Some people find it difficult to navigate and find what they are looking for.

MEDLINE is not free to use ( pricing information ).

Defunct Academic Search Engines 

#27. microsoft academic  .

Microsoft Academic

Microsoft Academic Search seemed to be a failure from the beginning. It ended in 2012, then re-launched in 2016 as Microsoft Academic. It provides the researcher with the opportunity to search academic publications,

Microsoft Academic used to be the second-largest academic search engine after Google Scholar. Microsoft Academic provides a wealth of data for free, but Microsoft has announced that it will shut Microsoft Academic down in by 2022. 

#28. Scizzle

Designed to help researchers stay on top of the literature by setting up email alerts, based on key terms, for newspapers.

Unfortunately, academic search engines come and go. These are two that are no longer available.

Final Thoughts

There are many academic search engines that can help researchers and scholars find the information they need. This list provides a variety of options, starting with more familiar engines and moving on to less well-known ones. 

Keeping an open mind and exploring different sources is essential for conducting effective online research. With so much information at our fingertips, it’s important to make sure we’re using the best tools available to us.

Tell us in the comment below which academic search engine have you not heard of? Which database do you think we should add? What database do your professional societies use? What are the most useful academic websites for research in your opinion?

There is more.

Check out our other articles on the Best Academic Tools Series for Research below.

• Learn how to get more done with these Academic Writing Tools  
• Learn how to proofread your work with these Proofreading Tools
• Learn how to broaden your research landscape with these Academic Search Engines
• Learn how to manage multiple research projects with these Project Management Tools
• Learn how to run effective survey research with these Survey Tools for Research
• Learn how get more insights from important conversations and interviews with Transcription Tools
• Learn how to manage the ever-growing list of references with these Reference Management Software
• Learn how to double your productivity with literature reviews with these AI-Based Summary Generators
• Learn how to build and develop your audience with these Academic Social Network Sites
• Learn how to make sure your content is original and trustworthy with these Plagiarism Checkers
• Learn how to talk about your work effectively with these Science Communication Tools

10 thoughts on “28 Best Academic Search Engines That make your research easier”

Thank you so much Joannah..I have found this information useful to me as librarian in an academic library

You are welcome! We are happy to hear that!

Thank You Team, for providing a comprehensive list of academic search engines that can help make research easier for students and scholars. The variety of search engines included offers a range of options for finding scholarly articles, journals, and other academic resources. The article also provides a brief summary of each search engine’s features, which helps in determining which one is the best fit for a specific research topic. Overall, this article is a valuable resource for anyone looking for a quick and easy way to access a wealth of academic information.

Thank you for taking the time to share your feedback with us. We are delighted to hear that you found our list of academic search engines helpful in making research easier for students and scholars. We understand the importance of having a variety of options when it comes to finding scholarly articles, journals, and other academic resources, and we strive to provide a comprehensive list of resources to meet those needs.

We are glad that you found the brief summary of each search engine’s features helpful in determining which one is the best fit for a specific research topic. Our goal is to make it easy for our readers to access valuable academic information and we’re glad that we were able to achieve that for you.

We appreciate your support and thank you for your kind words. We will continue to provide valuable resources for students and researchers in the future. Please let us know if you have any further questions or suggestions.

No more questions Thank You

I cannot thank you enough!!! thanks alot 🙂

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Hi Joannah! Here’s another one you may want to add! Expontum ( https://www.expontum.com/ ) – Helps researchers quickly find knowledge gaps and identify what research projects have been completed before. Thanks!

Expontum – Helps researchers quickly find knowledge gaps and identify what research projects have been completed before. Expontum is free, open access, and available to all globally with no paid versions of the site. Automated processes scan research article information 24/7 so this website is constantly updating. By looking at over 35 million research publications (240 million by the end of 2023), the site has 146 million tagged research subjects and 122 million tagged research attributes. Learn more about methodology and sources on the Expontum About Page ( https://www.expontum.com/about.php )

Hey Ryan, I clicked and checked your site and thought it was very relevant to our reader. Thank you for sharing. And, we will be reviewing your site soon.

Sounds good! Thanks, Joannah!

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

Need a helping hand?

Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications. If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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Tips for Online Students , Tips for Students

The Ultimate Student Guide To Finding Credible Sources

Updated: January 24, 2023

Published: January 1, 2020

When it comes to writing a research paper, it’s crucial that you use credible sources to make sure that the information you are stating is actually true. Knowing the difference between credible sources and unreliable sources doesn’t always come so easily with endless information flooding the internet. Thankfully, there are some simple tips that you can use to ensure that you are always using credible sources for research.

What is a Research Paper?

A research paper is a piece of academic writing that uses original research on a specific topic. There are many different types of research papers, ranging from a high school term paper to a master’s thesis or doctoral dissertation.

Photo by  Wallace Chuck  from  Pexels

How to start a search for sources, 1. start simple.

If you’re wondering how to find sources for a research paper, the easiest and best way to start is simple! Just try browsing through some common search engines to see what you find.

2. Cross Wikipedia off

Wikipedia, although it’s a massive pool of information, should always be avoided when writing a research paper since it allows the public to edit information. Sites such as these often run the risk of lacking accuracy, and is not one of the most credible sources for research.

3. Yes to scholarly databases

Scholarly databases are your best friend when it comes to finding credible sources for research. Online scholarly databases that can be trusted and are known to provide useful information for students include LexisNexis and EBSCO.

4. Newspapers and magazines

Although sometimes biased, newspapers and magazines can also be a great place to find information about current events.

5. The library

While the library seems to be the most obvious place to find information, somehow it’s often forgotten when it comes to research in the modern age. Don’t forget how useful it can truly be!

Types of Credible Sources for Research

1. what are some credible websites.

Many online sources do not necessarily contain information that is correct or has been checked. That’s why it’s of utmost importance to make sure that you’re using the right websites for your research, with government and educational websites generally being the most reliable.

Credible sources for research include: science.gov, The World Factbook, US Census Bureau, UK Statistics, and Encyclopedia Britannica.

2. What are some credible journal articles?

When it comes to journal articles, determining how credible they are comes much easier than other sources. This is generally due to the fact that many of these websites will include valuable information such as how many times the article has been cited, and if its been peer reviewed.

Some great examples of reliable websites for journal articles include Google Scholar, Oxford Academic, Microsoft Academic, Cornell University Library, and SAGE Publishing.

If you are ever not sure how to find credible sources, then there’s the CRAAP test, which takes into account the Currency, Relevance, Authority, Accuracy and Purpose of the article. Take all of these factors into consideration before using a source and determining whether or not it’s credible enough. Even if it takes more time, you’ll be saving yourself tons of time in the long run by not using unreliable sources.

Photo by  Canva Studio  from  Pexels

3. what are some credible news sources.

When it comes to news articles, more caution must be taken since it’s hard to know which sources are truly reliable and unbiased. The CRAAP test is also useful in this type of article for research.

A few examples of credible news sources include The New York Times, Bloomberg, and The Washington Post.

The Credibility of a Source

As you search for your research information, you will surely come across the question of how to find credible sources for a research paper. Here are some criteria to focus on to ensure that you only use the most credible of sources.

1. What’s the depth of it?

Always look at the depth of an article, not just the written content. See how long the article is, and if it contains the necessary information such as an abstract, a reference list, and documented data.

2. Who is reading it?

When judging the credibility of an article, it’s important to always ask yourself who the target audience of the article is. Sometimes, sources have a specific goal in mind and it can create certain biases.

3. What’s the goal?

Just as you should do with the audience, also ask yourself what the article is trying to achieve. What is their ultimate goal and how are they persuading you of that?

4. Who wrote it?

Always ask yourself who wrote the article and how reputable they are in the specific field. Look at what other published works they have as well.

5. Can it be trusted?

Overall, it’s key to ask yourself how reputable the source is. What kind of website is it published on? Look at the big picture.

6. Is it relevant to now?

Look at the date of the article, or about the specific things they are mentioning in the article. If it’s from a few years ago, it’s probably not too relevant to your current research.

7. Can it be proven?

While an article may sound incredibly convincing, many people have a way with words and persuasion. Stop and ask yourself whether or not what they are claiming can actually be proven.

Photo by  bruce mars  from  Pexels

How to evaluate source credibility.

By using unreliable sources in your research, it can discredit your status, which is why it’s incredibly important to make sure that any information you are using is up-to-date and accurate.

Here’s how to find credible sources.

1. What is a credible source?

Generally, materials that have been published within the past 10 years are considered to be credible sources for research. Another important factor to consider is the author — if they are well known and respected in their specific fields, that’s also generally a sign that the article is credible. Educational and government-run websites (.gov, .edu) tend to also be a safe source to use, as well as academic databases. Google Scholar is also a no-fail source for reliable information.

2. What is a potentially unreliable source?

Anything that is out of date, meaning it’s been published more than 10 years ago should be avoided. Materials published on social media platforms such as Facebook or personal blogs don’t tend to be the most credible. Always make sure that an article contains proper citations and that the website you are using ends in .com or .org.

Free Resources For Learning

There are many free resources for research available known as open educational resources . They are licensed for free use, with the intention of teaching. They can be determined as credible sources for research if they have a Creative Common license, and if the author has proven to be an expert in their field. Always make sure that the content you are using contains no biases.

Sites For Scholarly Research

When performing scholarly research, it’s extra important to make sure that your sources are credible. Government-run research is considered credible, but beware of any political sites. University and educational websites also tend to be reliable, but still take everything you read with a grain of salt. Company websites also tend to be reliable, although their ultimate goal is usually to promote a product. Organizations which are .org websites can be professional and reliable, however, sometimes they also have their own interests.

Which Sites Can Be Relied On

The internet has no shortage of information out there. That’s why you’ll need these handy tips to determine which to use, and how to distinguish through the vast choices without feeling overwhelmed.

List of Credible Research Sources to Consider

1. government entities.

These websites tend to be reliable since they are highly regulated. Examples include the CIA World Factbook and the United States Justice Statistics.

2. Research Think Tanks

Examples of reliable research think tanks include Rand Corporation, Pew Research Center and The Milken Institute.

3. Academic Libraries and Databases

ProQuest, Scopus, and Jstor are great examples of academic libraries and databases that can be trusted.

4. Professional Standards Organizations

The American Bar Association and The American Psychological Association (APA) are highly credible sources when it comes to professional standards.

How to Write a Research Paper: Step-by-Step

Now that you’re an expert on finding credible sources for research, you’re ready to go! But how do you even start to write a research paper? Don’t worry, we’ve got you covered.

For starters, it’s important to get clear instructions from your professor on what they want. The next step is to start brainstorming ideas for a topic of research. Once you’ve decided and feel confident about it, you’re ready to create your outline and plan out the goal of your research paper.

Befriend your librarian and start to search for quality and credible sources through a variety of means. Make sure you understand your topic from top to bottom before you start writing.  As you write, be sure to always keep things factual, and that you finalize your thesis statement throughout your paper — not just at the end. That’s what’s going to guide your writing. Be sure to always keep format in mind, never forget to cite your sources, and to never skip those edits and final checks.

Now you are ready to write a high-quality, fact-driven research paper that’s sure to impress your professors.

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Best Websites for Accessing Research Papers for Students

As a college student, you may have heard the phrase “research is important” thrown around by your professors all the time, but you may be wondering exactly why that is?

Not only does it help students better understand their chosen field of study, but it also allows them to develop important skills such as critical thinking, problem-solving, and communication.

In this article, we will be highlighting some of the best websites for accessing a wide range of research materials. Whether you’re looking for papers in a specific field or just want a general database of scholarly articles, these websites have got you covered.

Best Websites for Accessing Research Papers & Journals

The following are the best websites for college students to access research papers & journals:

1. Google Scholar

Google Scholar is a search engine that specifically searches for scholarly literature, including articles, books, theses, conference proceedings, etc. It is a free resource that can be accessed through the website, and it is available to anyone who is interested in finding research papers and other academic materials.

One of the benefits of using Google Scholar is that it searches a wide range of sources, including academic publishers, professional societies, online repositories, and universities. This means that you can find a diverse range of materials on a variety of topics.

Google Scholar also allows you to search for specific authors or institutions, and it provides tools to help you track your own research and manage your citations. You can also set up alerts to receive notifications when new research is published on a particular topic.

Pricing: Free

Access Research Papers Now

2. Microsoft Academic

Microsoft Academic is a free, public web search engine that allows users to search for academic papers, conferences, journals, and authors. It was developed by Microsoft and launched in 2012.

One of the key features of Microsoft Academic is its ability to search for papers based on the relationships between them. For example, you can use the website to find documents that have been cited by a particular research paper or research papers that have cited a particular research paper.

This can be a useful tool for researchers looking to discover new papers in their field or for students seeking additional resources for a research project.

Microsoft Academic also includes information about authors, conferences, and journals, and allows users to track their academic activity and achievements. Users can create their own profiles on the website and add their own papers to the database.

3. Science.gov

Science.gov is a website that provides access to over 60 databases, over 2,200 websites, and over 200 million pages of scientific and technical information from U.S. government agencies, including full-text documents, citations, scientific data supporting federally funded research, and multimedia.

It is a collaborative effort between various U.S. government agencies and is maintained by the U.S. Department of Energy’s Office of Scientific and Technical Information (OSTI).

Users can search for information using keywords or browse by topic. Science.gov is a useful resource for researchers, students, and anyone else interested in accessing scientific and technical information from U.S. government agencies.

4. ResearchGate

ResearchGate is a social networking site for scientists and researchers to share papers, ask and answer questions, and find collaborators. It was founded in 2008 by Ijad Madisch, Sören Hofmayer, and Horst Fickenscher. As of 2022, the website has over 20 million users from 190 countries, and hosts over 17 million research articles.

ResearchGate allows users to search for and access research papers for free, although some papers may be behind a paywall. The site also provides tools for researchers to manage their publications, track their impact, and connect with their peers. In addition to hosting research papers, ResearchGate also has a question and answer forum where users can ask and answer questions on various scientific topics.

Pricing: Free (some articles are behind a paywall)

BASE (Bielefeld Academic Search Engine) is a search engine for scholarly web resources, including research papers and journals. It was developed at Bielefeld University in Germany and is operated by the Bielefeld University Library.

BASE claims to be one of the most voluminous search engines for academic web resources, with over 300 million documents from more than 10,000 content providers. including research papers, theses, conference proceedings, and more.

The search engine is free to use and provides access to a wide range of academic content. In addition to searching for research papers, users can also use BASE to search for other types of academic resources, such as datasets, images, and videos.

Pricing: Free Access Research Papers Now

6. Directory of Open Access Journals

The Directory of Open Access Journals (DOAJ) is a digital library that provides access to free, full-text, peer-reviewed open access journals. Open access journals are scholarly journals that are available online and are free to access and read.

The DOAJ was launched in 2003 with the goal of increasing the visibility and accessibility of open access scientific and scholarly journals. It currently contains over 13,000 journals and more than 3.5 million articles.

The DOAJ is a not-for-profit organization that is supported by a number of organizations and individuals. It is run by a small team of staff and governed by a steering committee made up of representatives from the open access community.

7. Royal Society Open Science

The Royal Society Open Science is a peer-reviewed scientific journal that publishes original research across the natural and physical sciences. It is published by the Royal Society, which is a fellowship of the world’s most eminent scientists and the oldest scientific academy in continuous existence.

It is an open access journal, which means that all of its articles are available to read and download for free. All articles are subject to rigorous peer review to ensure the highest quality and standards.

The journal was established in 2014 with the goal of increasing transparency and reproducibility in scientific research. It has a broad scope and publishes research articles, reviews, letters, and perspectives. The journal covers a wide range of scientific disciplines, including biology, chemistry, physics, and engineering.

JSTOR (short for Journal Storage) is a digital library that provides online access to thousands of academic journals, books, and primary sources. It was founded in 1995 by William G. Bowen, then-president of the Andrew W. Mellon Foundation, as a way to digitize and preserve scholarly literature. JSTOR is a subscription-based service that provides access to its collections to libraries, institutions, and individuals.

JSTOR’s collections include more than 12 million academic journal articles, books, and primary sources in the arts, humanities, and social sciences. It also has a growing selection of ebooks and other resources in science, technology, and medicine.

JSTOR is known for its high-quality content and advanced search and discovery tools, which make it a popular resource for researchers and students.

Pricing: Subscription-based Access Research Papers Now

The websites listed above are just a few of the many options available for accessing research papers and journals. These websites can provide a wealth of knowledge and help you stay up-to-date on the latest research and developments in your field.

Be sure to check out the various options and see which one works best for your needs and budget.

Thirumoorthy

Thirumoorthy serves as a teacher and coach. He obtained a 99 percentile on the CAT. He cleared numerous IT jobs and public sector job interviews, but he still decided to pursue a career in education. He desires to elevate the underprivileged sections of society through education

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• Today, we’re introducing Meta Llama 3, the next generation of our state-of-the-art open source large language model.
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Today, we’re excited to share the first two models of the next generation of Llama, Meta Llama 3, available for broad use. This release features pretrained and instruction-fine-tuned language models with 8B and 70B parameters that can support a broad range of use cases. This next generation of Llama demonstrates state-of-the-art performance on a wide range of industry benchmarks and offers new capabilities, including improved reasoning. We believe these are the best open source models of their class, period. In support of our longstanding open approach, we’re putting Llama 3 in the hands of the community. We want to kickstart the next wave of innovation in AI across the stack—from applications to developer tools to evals to inference optimizations and more. We can’t wait to see what you build and look forward to your feedback.

Our goals for Llama 3

With Llama 3, we set out to build the best open models that are on par with the best proprietary models available today. We wanted to address developer feedback to increase the overall helpfulness of Llama 3 and are doing so while continuing to play a leading role on responsible use and deployment of LLMs. We are embracing the open source ethos of releasing early and often to enable the community to get access to these models while they are still in development. The text-based models we are releasing today are the first in the Llama 3 collection of models. Our goal in the near future is to make Llama 3 multilingual and multimodal, have longer context, and continue to improve overall performance across core LLM capabilities such as reasoning and coding.

State-of-the-art performance

Our new 8B and 70B parameter Llama 3 models are a major leap over Llama 2 and establish a new state-of-the-art for LLM models at those scales. Thanks to improvements in pretraining and post-training, our pretrained and instruction-fine-tuned models are the best models existing today at the 8B and 70B parameter scale. Improvements in our post-training procedures substantially reduced false refusal rates, improved alignment, and increased diversity in model responses. We also saw greatly improved capabilities like reasoning, code generation, and instruction following making Llama 3 more steerable.

*Please see evaluation details for setting and parameters with which these evaluations are calculated.

In the development of Llama 3, we looked at model performance on standard benchmarks and also sought to optimize for performance for real-world scenarios. To this end, we developed a new high-quality human evaluation set. This evaluation set contains 1,800 prompts that cover 12 key use cases: asking for advice, brainstorming, classification, closed question answering, coding, creative writing, extraction, inhabiting a character/persona, open question answering, reasoning, rewriting, and summarization. To prevent accidental overfitting of our models on this evaluation set, even our own modeling teams do not have access to it. The chart below shows aggregated results of our human evaluations across of these categories and prompts against Claude Sonnet, Mistral Medium, and GPT-3.5.

Preference rankings by human annotators based on this evaluation set highlight the strong performance of our 70B instruction-following model compared to competing models of comparable size in real-world scenarios.

Our pretrained model also establishes a new state-of-the-art for LLM models at those scales.

To develop a great language model, we believe it’s important to innovate, scale, and optimize for simplicity. We adopted this design philosophy throughout the Llama 3 project with a focus on four key ingredients: the model architecture, the pretraining data, scaling up pretraining, and instruction fine-tuning.

Model architecture

In line with our design philosophy, we opted for a relatively standard decoder-only transformer architecture in Llama 3. Compared to Llama 2, we made several key improvements. Llama 3 uses a tokenizer with a vocabulary of 128K tokens that encodes language much more efficiently, which leads to substantially improved model performance. To improve the inference efficiency of Llama 3 models, we’ve adopted grouped query attention (GQA) across both the 8B and 70B sizes. We trained the models on sequences of 8,192 tokens, using a mask to ensure self-attention does not cross document boundaries.

Training data

To train the best language model, the curation of a large, high-quality training dataset is paramount. In line with our design principles, we invested heavily in pretraining data. Llama 3 is pretrained on over 15T tokens that were all collected from publicly available sources. Our training dataset is seven times larger than that used for Llama 2, and it includes four times more code. To prepare for upcoming multilingual use cases, over 5% of the Llama 3 pretraining dataset consists of high-quality non-English data that covers over 30 languages. However, we do not expect the same level of performance in these languages as in English.

To ensure Llama 3 is trained on data of the highest quality, we developed a series of data-filtering pipelines. These pipelines include using heuristic filters, NSFW filters, semantic deduplication approaches, and text classifiers to predict data quality. We found that previous generations of Llama are surprisingly good at identifying high-quality data, hence we used Llama 2 to generate the training data for the text-quality classifiers that are powering Llama 3.

We also performed extensive experiments to evaluate the best ways of mixing data from different sources in our final pretraining dataset. These experiments enabled us to select a data mix that ensures that Llama 3 performs well across use cases including trivia questions, STEM, coding, historical knowledge, etc.

Scaling up pretraining

To effectively leverage our pretraining data in Llama 3 models, we put substantial effort into scaling up pretraining. Specifically, we have developed a series of detailed scaling laws for downstream benchmark evaluations. These scaling laws enable us to select an optimal data mix and to make informed decisions on how to best use our training compute. Importantly, scaling laws allow us to predict the performance of our largest models on key tasks (for example, code generation as evaluated on the HumanEval benchmark—see above) before we actually train the models. This helps us ensure strong performance of our final models across a variety of use cases and capabilities.

We made several new observations on scaling behavior during the development of Llama 3. For example, while the Chinchilla-optimal amount of training compute for an 8B parameter model corresponds to ~200B tokens, we found that model performance continues to improve even after the model is trained on two orders of magnitude more data. Both our 8B and 70B parameter models continued to improve log-linearly after we trained them on up to 15T tokens. Larger models can match the performance of these smaller models with less training compute, but smaller models are generally preferred because they are much more efficient during inference.

To train our largest Llama 3 models, we combined three types of parallelization: data parallelization, model parallelization, and pipeline parallelization. Our most efficient implementation achieves a compute utilization of over 400 TFLOPS per GPU when trained on 16K GPUs simultaneously. We performed training runs on two custom-built 24K GPU clusters . To maximize GPU uptime, we developed an advanced new training stack that automates error detection, handling, and maintenance. We also greatly improved our hardware reliability and detection mechanisms for silent data corruption, and we developed new scalable storage systems that reduce overheads of checkpointing and rollback. Those improvements resulted in an overall effective training time of more than 95%. Combined, these improvements increased the efficiency of Llama 3 training by ~three times compared to Llama 2.

Instruction fine-tuning

To fully unlock the potential of our pretrained models in chat use cases, we innovated on our approach to instruction-tuning as well. Our approach to post-training is a combination of supervised fine-tuning (SFT), rejection sampling, proximal policy optimization (PPO), and direct preference optimization (DPO). The quality of the prompts that are used in SFT and the preference rankings that are used in PPO and DPO has an outsized influence on the performance of aligned models. Some of our biggest improvements in model quality came from carefully curating this data and performing multiple rounds of quality assurance on annotations provided by human annotators.

Learning from preference rankings via PPO and DPO also greatly improved the performance of Llama 3 on reasoning and coding tasks. We found that if you ask a model a reasoning question that it struggles to answer, the model will sometimes produce the right reasoning trace: The model knows how to produce the right answer, but it does not know how to select it. Training on preference rankings enables the model to learn how to select it.

Building with Llama 3

Our vision is to enable developers to customize Llama 3 to support relevant use cases and to make it easier to adopt best practices and improve the open ecosystem. With this release, we’re providing new trust and safety tools including updated components with both Llama Guard 2 and Cybersec Eval 2, and the introduction of Code Shield—an inference time guardrail for filtering insecure code produced by LLMs.

We’ve also co-developed Llama 3 with torchtune , the new PyTorch-native library for easily authoring, fine-tuning, and experimenting with LLMs. torchtune provides memory efficient and hackable training recipes written entirely in PyTorch. The library is integrated with popular platforms such as Hugging Face, Weights & Biases, and EleutherAI and even supports Executorch for enabling efficient inference to be run on a wide variety of mobile and edge devices. For everything from prompt engineering to using Llama 3 with LangChain we have a comprehensive getting started guide and takes you from downloading Llama 3 all the way to deployment at scale within your generative AI application.

A system-level approach to responsibility

We have designed Llama 3 models to be maximally helpful while ensuring an industry leading approach to responsibly deploying them. To achieve this, we have adopted a new, system-level approach to the responsible development and deployment of Llama. We envision Llama models as part of a broader system that puts the developer in the driver’s seat. Llama models will serve as a foundational piece of a system that developers design with their unique end goals in mind.

Instruction fine-tuning also plays a major role in ensuring the safety of our models. Our instruction-fine-tuned models have been red-teamed (tested) for safety through internal and external efforts. ​​Our red teaming approach leverages human experts and automation methods to generate adversarial prompts that try to elicit problematic responses. For instance, we apply comprehensive testing to assess risks of misuse related to Chemical, Biological, Cyber Security, and other risk areas. All of these efforts are iterative and used to inform safety fine-tuning of the models being released. You can read more about our efforts in the model card .

Llama Guard models are meant to be a foundation for prompt and response safety and can easily be fine-tuned to create a new taxonomy depending on application needs. As a starting point, the new Llama Guard 2 uses the recently announced MLCommons taxonomy, in an effort to support the emergence of industry standards in this important area. Additionally, CyberSecEval 2 expands on its predecessor by adding measures of an LLM’s propensity to allow for abuse of its code interpreter, offensive cybersecurity capabilities, and susceptibility to prompt injection attacks (learn more in our technical paper ). Finally, we’re introducing Code Shield which adds support for inference-time filtering of insecure code produced by LLMs. This offers mitigation of risks around insecure code suggestions, code interpreter abuse prevention, and secure command execution.

With the speed at which the generative AI space is moving, we believe an open approach is an important way to bring the ecosystem together and mitigate these potential harms. As part of that, we’re updating our Responsible Use Guide (RUG) that provides a comprehensive guide to responsible development with LLMs. As we outlined in the RUG, we recommend that all inputs and outputs be checked and filtered in accordance with content guidelines appropriate to the application. Additionally, many cloud service providers offer content moderation APIs and other tools for responsible deployment, and we encourage developers to also consider using these options.

Deploying Llama 3 at scale

Llama 3 will soon be available on all major platforms including cloud providers, model API providers, and much more. Llama 3 will be everywhere .

Our benchmarks show the tokenizer offers improved token efficiency, yielding up to 15% fewer tokens compared to Llama 2. Also, Group Query Attention (GQA) now has been added to Llama 3 8B as well. As a result, we observed that despite the model having 1B more parameters compared to Llama 2 7B, the improved tokenizer efficiency and GQA contribute to maintaining the inference efficiency on par with Llama 2 7B.

For examples of how to leverage all of these capabilities, check out Llama Recipes which contains all of our open source code that can be leveraged for everything from fine-tuning to deployment to model evaluation.

What’s next for Llama 3?

The Llama 3 8B and 70B models mark the beginning of what we plan to release for Llama 3. And there’s a lot more to come.

Our largest models are over 400B parameters and, while these models are still training, our team is excited about how they’re trending. Over the coming months, we’ll release multiple models with new capabilities including multimodality, the ability to converse in multiple languages, a much longer context window, and stronger overall capabilities. We will also publish a detailed research paper once we are done training Llama 3.

To give you a sneak preview for where these models are today as they continue training, we thought we could share some snapshots of how our largest LLM model is trending. Please note that this data is based on an early checkpoint of Llama 3 that is still training and these capabilities are not supported as part of the models released today.

We’re committed to the continued growth and development of an open AI ecosystem for releasing our models responsibly. We have long believed that openness leads to better, safer products, faster innovation, and a healthier overall market. This is good for Meta, and it is good for society. We’re taking a community-first approach with Llama 3, and starting today, these models are available on the leading cloud, hosting, and hardware platforms with many more to come.

Try Meta Llama 3 today

We’ve integrated our latest models into Meta AI, which we believe is the world’s leading AI assistant. It’s now built with Llama 3 technology and it’s available in more countries across our apps.

You can use Meta AI on Facebook, Instagram, WhatsApp, Messenger, and the web to get things done, learn, create, and connect with the things that matter to you. You can read more about the Meta AI experience here .

Visit the Llama 3 website to download the models and reference the Getting Started Guide for the latest list of all available platforms.

You’ll also soon be able to test multimodal Meta AI on our Ray-Ban Meta smart glasses.

As always, we look forward to seeing all the amazing products and experiences you will build with Meta Llama 3.

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