Stand on the shoulders of giants

Google Scholar provides a simple way to broadly search for scholarly literature. From one place, you can search across many disciplines and sources: articles, theses, books, abstracts and court opinions, from academic publishers, professional societies, online repositories, universities and other web sites. Google Scholar helps you find relevant work across the world of scholarly research.

research paper about google

How are documents ranked?

Google Scholar aims to rank documents the way researchers do, weighing the full text of each document, where it was published, who it was written by, as well as how often and how recently it has been cited in other scholarly literature.

Features of Google Scholar

  • Search all scholarly literature from one convenient place
  • Explore related works, citations, authors, and publications
  • Locate the complete document through your library or on the web
  • Keep up with recent developments in any area of research
  • Check who's citing your publications, create a public author profile

research paper about google

Disclaimer: Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

  • Privacy & Terms

18 Google Scholar tips all students should know

Dec 13, 2022

[[read-time]] min read

Think of this guide as your personal research assistant.

Molly McHugh-Johnson headshot

“It’s hard to pick your favorite kid,” Anurag Acharya says when I ask him to talk about a favorite Google Scholar feature he’s worked on. “I work on product, engineering, operations, partnerships,” he says. He’s been doing it for 18 years, which as of this month, happens to be how long Google Scholar has been around.

Google Scholar is also one of Google’s longest-running services. The comprehensive database of research papers, legal cases and other scholarly publications was the fourth Search service Google launched, Anurag says. In honor of this very important tool’s 18th anniversary, I asked Anurag to share 18 things you can do in Google Scholar that you might have missed.

1. Copy article citations in the style of your choice.

With a simple click of the cite button (which sits below an article entry), Google Scholar will give you a ready-to-use citation for the article in five styles, including APA, MLA and Chicago. You can select and copy the one you prefer.

2. Dig deeper with related searches.

Google Scholar’s related searches can help you pinpoint your research; you’ll see them show up on a page in between article results. Anurag describes it like this: You start with a big topic — like “cancer” — and follow up with a related search like “lung cancer” or “colon cancer” to explore specific kinds of cancer.

A Google Scholar search results page for “cancer.” After four search results, there is a section of Related searches, including breast cancer, lung cancer, prostate cancer, colorectal cancer, cervical cancer, colon cancer, cancer chemotherapy and ovarian cancer.

Related searches can help you find what you’re looking for.

3. And don’t miss the related articles.

This is another great way to find more papers similar to one you found helpful — you can find this link right below an entry.

4. Read the papers you find.

Scholarly articles have long been available only by subscription. To keep you from having to log in every time you see a paper you’re interested in, Scholar works with libraries and publishers worldwide to integrate their subscriptions directly into its search results. Look for a link marked [PDF] or [HTML]. This also includes preprints and other free-to-read versions of papers.

5. Access Google Scholar tools from anywhere on the web with the Scholar Button browser extension.

The Scholar Button browser extension is sort of like a mini version of Scholar that can move around the web with you. If you’re searching for something, hitting the extension icon will show you studies about that topic, and if you’re reading a study, you can hit that same button to find a version you read, create a citation or to save it to your Scholar library.

A screenshot of a Google Search results landing page, with the Scholar Button extension clicked. The user has searched for “breast cancer” within Google Search; that term is also searched in the Google Scholar extension. The extension shows three relevant articles from Google Scholar.

Install the Scholar Button Chrome browser extension to access Google Scholar from anywhere on the web.

6. Learn more about authors through Scholar profiles.

There are many times when you’ll want to know more about the researchers behind the ideas you’re looking into. You can do this by clicking on an author’s name when it’s hyperlinked in a search result. You’ll find all of their work as well as co-authors, articles they’re cited in and so on. You can also follow authors from their Scholar profile to get email updates about their work, or about when and where their work is cited.

7. Easily find topic experts.

One last thing about author profiles: If there are topics listed below an author’s name on their profile, you can click on these areas of expertise and you’ll see a page of more authors who are researching and publishing on these topics, too.

8. Search for court opinions with the “Case law” button.

Scholar is the largest free database of U.S. court opinions. When you search for something using Google Scholar, you can select the “Case law” button below the search box to see legal cases your keywords are referenced in. You can read the opinions and a summary of what they established.

9. See how those court opinions have been cited.

If you want to better understand the impact of a particular piece of case law, you can select “How Cited,” which is below an entry, to see how and where the document has been cited. For example, here is the How Cited page for Marbury v. Madison , a landmark U.S. Supreme Court ruling that established that courts can strike down unconstitutional laws or statutes.

10. Understand how a legal opinion depends on another.

When you’re looking at how case laws are cited within Google Scholar, click on “Cited by” and check out the horizontal bars next to the different results. They indicate how relevant the cited opinion is in the court decision it’s cited within. You will see zero, one, two or three bars before each result. Those bars indicate the extent to which the new opinion depends on and refers to the cited case.

A screenshot of the “Cited by” page for U.S. Supreme Court case New York Times Company v. Sullivan. The Cited by page shows four different cases; two of them have three bars filled in, indicating they rely heavily on New York Times Company v. Sullivan; the other two cases only have one bar filled in, indicating less reliance on New York Times Company v. Sullivan.

In the Cited by page for New York Times Company v. Sullivan, court cases with three bars next to their name heavily reference the original case. One bar indicates less reliance.

11. Sign up for Google Scholar alerts.

Want to stay up to date on a specific topic? Create an alert for a Google Scholar search for your topics and you’ll get email updates similar to Google Search alerts. Another way to keep up with research in your area is to follow new articles by leading researchers. Go to their profiles and click “Follow.” If you’re a junior grad student, you may consider following articles related to your advisor’s research topics, for instance.

12. Save interesting articles to your library.

It’s easy to go down fascinating rabbit hole after rabbit hole in Google Scholar. Don’t lose track of your research and use the save option that pops up under search results so articles will be in your library for later reading.

13. Keep your library organized with labels.

Labels aren’t only for Gmail! You can create labels within your Google Scholar library so you can keep your research organized. Click on “My library,” and then the “Manage labels…” option to create a new label.

14. If you’re a researcher, share your research with all your colleagues.

Many research funding agencies around the world now mandate that funded articles should become publicly free to read within a year of publication — or sooner. Scholar profiles list such articles to help researchers keep track of them and open up access to ones that are still locked down. That means you can immediately see what is currently available from researchers you’re interested in and how many of their papers will soon be publicly free to read.

15. Look through Scholar’s annual top publications and papers.

Every year, Google Scholar releases the top publications based on the most-cited papers. That list (available in 11 languages) will also take you to each publication’s top papers — this takes into account the “h index,” which measures how much impact an article has had. It’s an excellent place to start a research journey as well as get an idea about the ideas and discoveries researchers are currently focused on.

16. Get even more specific with Advanced Search.

Click on the hamburger icon on the upper left-hand corner and select Advanced Search to fine-tune your queries. For example, articles with exact words or a particular phrase in the title or articles from a particular journal and so on.

17. Find extra help on Google Scholar’s help page.

It might sound obvious, but there’s a wealth of useful information to be found here — like how often the database is updated, tips on formatting searches and how you can use your library subscriptions when you’re off-campus (looking at you, college students!). Oh, and you’ll even learn the origin of that quote on Google Scholar’s home page.

The Google Scholar home page. The quote at the bottom reads: “Stand on the shoulders of giants.”

18. Keep up with Google Scholar news.

Don’t forget to check out the Google Scholar blog for updates on new features and tips for using this tool even better.

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  • Corrections

Search Help

Get the most out of Google Scholar with some helpful tips on searches, email alerts, citation export, and more.

Finding recent papers

Your search results are normally sorted by relevance, not by date. To find newer articles, try the following options in the left sidebar:

  • click "Since Year" to show only recently published papers, sorted by relevance;
  • click "Sort by date" to show just the new additions, sorted by date;
  • click the envelope icon to have new results periodically delivered by email.

Locating the full text of an article

Abstracts are freely available for most of the articles. Alas, reading the entire article may require a subscription. Here're a few things to try:

  • click a library link, e.g., "FindIt@Harvard", to the right of the search result;
  • click a link labeled [PDF] to the right of the search result;
  • click "All versions" under the search result and check out the alternative sources;
  • click "Related articles" or "Cited by" under the search result to explore similar articles.

If you're affiliated with a university, but don't see links such as "FindIt@Harvard", please check with your local library about the best way to access their online subscriptions. You may need to do search from a computer on campus, or to configure your browser to use a library proxy.

Getting better answers

If you're new to the subject, it may be helpful to pick up the terminology from secondary sources. E.g., a Wikipedia article for "overweight" might suggest a Scholar search for "pediatric hyperalimentation".

If the search results are too specific for your needs, check out what they're citing in their "References" sections. Referenced works are often more general in nature.

Similarly, if the search results are too basic for you, click "Cited by" to see newer papers that referenced them. These newer papers will often be more specific.

Explore! There's rarely a single answer to a research question. Click "Related articles" or "Cited by" to see closely related work, or search for author's name and see what else they have written.

Searching Google Scholar

Use the "author:" operator, e.g., author:"d knuth" or author:"donald e knuth".

Put the paper's title in quotations: "A History of the China Sea".

You'll often get better results if you search only recent articles, but still sort them by relevance, not by date. E.g., click "Since 2018" in the left sidebar of the search results page.

To see the absolutely newest articles first, click "Sort by date" in the sidebar. If you use this feature a lot, you may also find it useful to setup email alerts to have new results automatically sent to you.

Note: On smaller screens that don't show the sidebar, these options are available in the dropdown menu labelled "Year" right below the search button.

Select the "Case law" option on the homepage or in the side drawer on the search results page.

It finds documents similar to the given search result.

It's in the side drawer. The advanced search window lets you search in the author, title, and publication fields, as well as limit your search results by date.

Select the "Case law" option and do a keyword search over all jurisdictions. Then, click the "Select courts" link in the left sidebar on the search results page.

Tip: To quickly search a frequently used selection of courts, bookmark a search results page with the desired selection.

Access to articles

For each Scholar search result, we try to find a version of the article that you can read. These access links are labelled [PDF] or [HTML] and appear to the right of the search result. For example:

A paper that you need to read

Access links cover a wide variety of ways in which articles may be available to you - articles that your library subscribes to, open access articles, free-to-read articles from publishers, preprints, articles in repositories, etc.

When you are on a campus network, access links automatically include your library subscriptions and direct you to subscribed versions of articles. On-campus access links cover subscriptions from primary publishers as well as aggregators.

Off-campus access

Off-campus access links let you take your library subscriptions with you when you are at home or traveling. You can read subscribed articles when you are off-campus just as easily as when you are on-campus. Off-campus access links work by recording your subscriptions when you visit Scholar while on-campus, and looking up the recorded subscriptions later when you are off-campus.

We use the recorded subscriptions to provide you with the same subscribed access links as you see on campus. We also indicate your subscription access to participating publishers so that they can allow you to read the full-text of these articles without logging in or using a proxy. The recorded subscription information expires after 30 days and is automatically deleted.

In addition to Google Scholar search results, off-campus access links can also appear on articles from publishers participating in the off-campus subscription access program. Look for links labeled [PDF] or [HTML] on the right hand side of article pages.

Anne Author , John Doe , Jane Smith , Someone Else

In this fascinating paper, we investigate various topics that would be of interest to you. We also describe new methods relevant to your project, and attempt to address several questions which you would also like to know the answer to. Lastly, we analyze …

You can disable off-campus access links on the Scholar settings page . Disabling off-campus access links will turn off recording of your library subscriptions. It will also turn off indicating subscription access to participating publishers. Once off-campus access links are disabled, you may need to identify and configure an alternate mechanism (e.g., an institutional proxy or VPN) to access your library subscriptions while off-campus.

Email Alerts

Do a search for the topic of interest, e.g., "M Theory"; click the envelope icon in the sidebar of the search results page; enter your email address, and click "Create alert". We'll then periodically email you newly published papers that match your search criteria.

No, you can enter any email address of your choice. If the email address isn't a Google account or doesn't match your Google account, then we'll email you a verification link, which you'll need to click to start receiving alerts.

This works best if you create a public profile , which is free and quick to do. Once you get to the homepage with your photo, click "Follow" next to your name, select "New citations to my articles", and click "Done". We will then email you when we find new articles that cite yours.

Search for the title of your paper, e.g., "Anti de Sitter space and holography"; click on the "Cited by" link at the bottom of the search result; and then click on the envelope icon in the left sidebar of the search results page.

First, do a search for your colleague's name, and see if they have a Scholar profile. If they do, click on it, click the "Follow" button next to their name, select "New articles by this author", and click "Done".

If they don't have a profile, do a search by author, e.g., [author:s-hawking], and click on the mighty envelope in the left sidebar of the search results page. If you find that several different people share the same name, you may need to add co-author names or topical keywords to limit results to the author you wish to follow.

We send the alerts right after we add new papers to Google Scholar. This usually happens several times a week, except that our search robots meticulously observe holidays.

There's a link to cancel the alert at the bottom of every notification email.

If you created alerts using a Google account, you can manage them all here . If you're not using a Google account, you'll need to unsubscribe from the individual alerts and subscribe to the new ones.

Google Scholar library

Google Scholar library is your personal collection of articles. You can save articles right off the search page, organize them by adding labels, and use the power of Scholar search to quickly find just the one you want - at any time and from anywhere. You decide what goes into your library, and we’ll keep the links up to date.

You get all the goodies that come with Scholar search results - links to PDF and to your university's subscriptions, formatted citations, citing articles, and more!

Library help

Find the article you want to add in Google Scholar and click the “Save” button under the search result.

Click “My library” at the top of the page or in the side drawer to view all articles in your library. To search the full text of these articles, enter your query as usual in the search box.

Find the article you want to remove, and then click the “Delete” button under it.

  • To add a label to an article, find the article in your library, click the “Label” button under it, select the label you want to apply, and click “Done”.
  • To view all the articles with a specific label, click the label name in the left sidebar of your library page.
  • To remove a label from an article, click the “Label” button under it, deselect the label you want to remove, and click “Done”.
  • To add, edit, or delete labels, click “Manage labels” in the left column of your library page.

Only you can see the articles in your library. If you create a Scholar profile and make it public, then the articles in your public profile (and only those articles) will be visible to everyone.

Your profile contains all the articles you have written yourself. It’s a way to present your work to others, as well as to keep track of citations to it. Your library is a way to organize the articles that you’d like to read or cite, not necessarily the ones you’ve written.

Citation Export

Click the "Cite" button under the search result and then select your bibliography manager at the bottom of the popup. We currently support BibTeX, EndNote, RefMan, and RefWorks.

Err, no, please respect our robots.txt when you access Google Scholar using automated software. As the wearers of crawler's shoes and webmaster's hat, we cannot recommend adherence to web standards highly enough.

Sorry, we're unable to provide bulk access. You'll need to make an arrangement directly with the source of the data you're interested in. Keep in mind that a lot of the records in Google Scholar come from commercial subscription services.

Sorry, we can only show up to 1,000 results for any particular search query. Try a different query to get more results.

Content Coverage

Google Scholar includes journal and conference papers, theses and dissertations, academic books, pre-prints, abstracts, technical reports and other scholarly literature from all broad areas of research. You'll find works from a wide variety of academic publishers, professional societies and university repositories, as well as scholarly articles available anywhere across the web. Google Scholar also includes court opinions and patents.

We index research articles and abstracts from most major academic publishers and repositories worldwide, including both free and subscription sources. To check current coverage of a specific source in Google Scholar, search for a sample of their article titles in quotes.

While we try to be comprehensive, it isn't possible to guarantee uninterrupted coverage of any particular source. We index articles from sources all over the web and link to these websites in our search results. If one of these websites becomes unavailable to our search robots or to a large number of web users, we have to remove it from Google Scholar until it becomes available again.

Our meticulous search robots generally try to index every paper from every website they visit, including most major sources and also many lesser known ones.

That said, Google Scholar is primarily a search of academic papers. Shorter articles, such as book reviews, news sections, editorials, announcements and letters, may or may not be included. Untitled documents and documents without authors are usually not included. Website URLs that aren't available to our search robots or to the majority of web users are, obviously, not included either. Nor do we include websites that require you to sign up for an account, install a browser plugin, watch four colorful ads, and turn around three times and say coo-coo before you can read the listing of titles scanned at 10 DPI... You get the idea, we cover academic papers from sensible websites.

That's usually because we index many of these papers from other websites, such as the websites of their primary publishers. The "site:" operator currently only searches the primary version of each paper.

It could also be that the papers are located on examplejournals.gov, not on example.gov. Please make sure you're searching for the "right" website.

That said, the best way to check coverage of a specific source is to search for a sample of their papers using the title of the paper.

Ahem, we index papers, not journals. You should also ask about our coverage of universities, research groups, proteins, seminal breakthroughs, and other dimensions that are of interest to users. All such questions are best answered by searching for a statistical sample of papers that has the property of interest - journal, author, protein, etc. Many coverage comparisons are available if you search for [allintitle:"google scholar"], but some of them are more statistically valid than others.

Currently, Google Scholar allows you to search and read published opinions of US state appellate and supreme court cases since 1950, US federal district, appellate, tax and bankruptcy courts since 1923 and US Supreme Court cases since 1791. In addition, it includes citations for cases cited by indexed opinions or journal articles which allows you to find influential cases (usually older or international) which are not yet online or publicly available.

Legal opinions in Google Scholar are provided for informational purposes only and should not be relied on as a substitute for legal advice from a licensed lawyer. Google does not warrant that the information is complete or accurate.

We normally add new papers several times a week. However, updates to existing records take 6-9 months to a year or longer, because in order to update our records, we need to first recrawl them from the source website. For many larger websites, the speed at which we can update their records is limited by the crawl rate that they allow.

Inclusion and Corrections

We apologize, and we assure you the error was unintentional. Automated extraction of information from articles in diverse fields can be tricky, so an error sometimes sneaks through.

Please write to the owner of the website where the erroneous search result is coming from, and encourage them to provide correct bibliographic data to us, as described in the technical guidelines . Once the data is corrected on their website, it usually takes 6-9 months to a year or longer for it to be updated in Google Scholar. We appreciate your help and your patience.

If you can't find your papers when you search for them by title and by author, please refer your publisher to our technical guidelines .

You can also deposit your papers into your institutional repository or put their PDF versions on your personal website, but please follow your publisher's requirements when you do so. See our technical guidelines for more details on the inclusion process.

We normally add new papers several times a week; however, it might take us some time to crawl larger websites, and corrections to already included papers can take 6-9 months to a year or longer.

Google Scholar generally reflects the state of the web as it is currently visible to our search robots and to the majority of users. When you're searching for relevant papers to read, you wouldn't want it any other way!

If your citation counts have gone down, chances are that either your paper or papers that cite it have either disappeared from the web entirely, or have become unavailable to our search robots, or, perhaps, have been reformatted in a way that made it difficult for our automated software to identify their bibliographic data and references. If you wish to correct this, you'll need to identify the specific documents with indexing problems and ask your publisher to fix them. Please refer to the technical guidelines .

Please do let us know . Please include the URL for the opinion, the corrected information and a source where we can verify the correction.

We're only able to make corrections to court opinions that are hosted on our own website. For corrections to academic papers, books, dissertations and other third-party material, click on the search result in question and contact the owner of the website where the document came from. For corrections to books from Google Book Search, click on the book's title and locate the link to provide feedback at the bottom of the book's page.

General Questions

These are articles which other scholarly articles have referred to, but which we haven't found online. To exclude them from your search results, uncheck the "include citations" box on the left sidebar.

First, click on links labeled [PDF] or [HTML] to the right of the search result's title. Also, check out the "All versions" link at the bottom of the search result.

Second, if you're affiliated with a university, using a computer on campus will often let you access your library's online subscriptions. Look for links labeled with your library's name to the right of the search result's title. Also, see if there's a link to the full text on the publisher's page with the abstract.

Keep in mind that final published versions are often only available to subscribers, and that some articles are not available online at all. Good luck!

Technically, your web browser remembers your settings in a "cookie" on your computer's disk, and sends this cookie to our website along with every search. Check that your browser isn't configured to discard our cookies. Also, check if disabling various proxies or overly helpful privacy settings does the trick. Either way, your settings are stored on your computer, not on our servers, so a long hard look at your browser's preferences or internet options should help cure the machine's forgetfulness.

Not even close. That phrase is our acknowledgement that much of scholarly research involves building on what others have already discovered. It's taken from Sir Isaac Newton's famous quote, "If I have seen further, it is by standing on the shoulders of giants."

  • Privacy & Terms

unprecedented photorealism × deep level of language understanding

Unprecedented photorealism, deep level of language understanding.

Google Research, Brain Team

We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation. Our key discovery is that generic large language models (e.g. T5), pretrained on text-only corpora, are surprisingly effective at encoding text for image synthesis: increasing the size of the language model in Imagen boosts both sample fidelity and image-text alignment much more than increasing the size of the image diffusion model. Imagen achieves a new state-of-the-art FID score of 7.27 on the COCO dataset, without ever training on COCO, and human raters find Imagen samples to be on par with the COCO data itself in image-text alignment. To assess text-to-image models in greater depth, we introduce DrawBench, a comprehensive and challenging benchmark for text-to-image models. With DrawBench, we compare Imagen with recent methods including VQ-GAN+CLIP, Latent Diffusion Models, and DALL-E 2, and find that human raters prefer Imagen over other models in side-by-side comparisons, both in terms of sample quality and image-text alignment.

More from the Imagen family:

research paper about google

Imagen is an AI system that creates photorealistic images from input text

research paper about google

Visualization of Imagen. Imagen uses a large frozen T5-XXL encoder to encode the input text into embeddings. A conditional diffusion model maps the text embedding into a 64×64 image. Imagen further utilizes text-conditional super-resolution diffusion models to upsample the image 64×64→256×256 and 256×256→1024×1024.

Large Pretrained Language Model × Cascaded Diffusion Model

Deep textual understanding → photorealistic generation, imagen research highlights.

  • We show that large pretrained frozen text encoders are very effective for the text-to-image task.
  • We show that scaling the pretrained text encoder size is more important than scaling the diffusion model size.
  • We introduce a new thresholding diffusion sampler, which enables the use of very large classifier-free guidance weights.
  • We introduce a new Efficient U-Net architecture, which is more compute efficient, more memory efficient, and converges faster.
  • On COCO, we achieve a new state-of-the-art COCO FID of 7.27; and human raters find Imagen samples to be on-par with reference images in terms of image-text alignment.

DrawBench: new comprehensive challenging benchmark

  • Side-by-side human evaluation.
  • Systematically test for: compositionality, cardinality, spatial relations, long-form text, rare words, and challenging prompts.
  • Human raters strongly prefer Imagen over other methods, in both image-text alignment and image fidelity.

State-of-the-art text-to-image

#1 in coco fid · #1 in drawbench.

Click on a word below and Imagen!

wearing a cowboy hat and wearing a sunglasses and

red shirt black leather jacket

playing a guitar riding a bike skateboarding

in a garden. on a beach. on top of a mountain.

Related Work

Diffusion models have seen wide success in image generation [ 1 , 2 , 3 , 4 ]. Autoregressive models [ 5 ], GANs [ 6 , 7 ] VQ-VAE Transformer based methods [ 8 , 9 ] have all made remarkable progress in text-to-image research. More recently, Diffusion models have been explored for text-to-image generation [ 10 , 11 ], including the concurrent work of DALL-E 2 [ 12 ]. DALL-E 2 uses a diffusion prior on CLIP latents, and cascaded diffusion models to generate high resolution 1024×1024 images. We believe Imagen is much simpler, as Imagen does not need to learn a latent prior, yet achieves better results in both MS-COCO FID and side-by-side human evaluation on DrawBench. GLIDE [ 10 ] also uses cascaded diffusions models for text-to-image, but Imagen uses larger pretrained frozen language models, which we found to be instrumental to both image fidelity and image-text alignment. XMC-GAN [ 7 ] also uses BERT as a text encoder, but we scale to much larger text encoders and demonstrate the effectiveness thereof. The use of cascaded diffusion models is also popular throughout the literature [ 13 , 14 ], and has been used with success in diffusion models to generate high resolution images [ 2 , 3 ]. Finally, Imagen is part of a series of text-to-image work at Google Research, including its sibling model Parti .

Limitations and Societal Impact

There are several ethical challenges facing text-to-image research broadly. We offer a more detailed exploration of these challenges in our paper and offer a summarized version here. First, downstream applications of text-to-image models are varied and may impact society in complex ways. The potential risks of misuse raise concerns regarding responsible open-sourcing of code and demos. At this time we have decided not to release code or a public demo. In future work we will explore a framework for responsible externalization that balances the value of external auditing with the risks of unrestricted open-access. Second, the data requirements of text-to-image models have led researchers to rely heavily on large, mostly uncurated, web-scraped datasets. While this approach has enabled rapid algorithmic advances in recent years, datasets of this nature often reflect social stereotypes, oppressive viewpoints, and derogatory, or otherwise harmful, associations to marginalized identity groups. While a subset of our training data was filtered to removed noise and undesirable content, such as pornographic imagery and toxic language, we also utilized LAION-400M dataset which is known to contain a wide range of inappropriate content including pornographic imagery, racist slurs, and harmful social stereotypes. Imagen relies on text encoders trained on uncurated web-scale data, and thus inherits the social biases and limitations of large language models. As such, there is a risk that Imagen has encoded harmful stereotypes and representations, which guides our decision to not release Imagen for public use without further safeguards in place.

Finally, while there has been extensive work auditing image-to-text and image labeling models for forms of social bias, there has been comparatively less work on social bias evaluation methods for text-to-image models. A conceptual vocabulary around potential harms of text-to-image models and established metrics of evaluation are an essential component of establishing responsible model release practices. While we leave an in-depth empirical analysis of social and cultural biases to future work, our small scale internal assessments reveal several limitations that guide our decision not to release our model at this time.  Imagen, may run into danger of dropping modes of the data distribution, which may further compound the social consequence of dataset bias. Imagen exhibits serious limitations when generating images depicting people. Our human evaluations found Imagen obtains significantly higher preference rates when evaluated on images that do not portray people, indicating  a degradation in image fidelity. Preliminary assessment also suggests Imagen encodes several social biases and stereotypes, including an overall bias towards generating images of people with lighter skin tones and a tendency for images portraying different professions to align with Western gender stereotypes. Finally, even when we focus generations away from people, our preliminary analysis indicates Imagen encodes a range of social and cultural biases when generating images of activities, events, and objects. We aim to make progress on several of these open challenges and limitations in future work.

research paper about google

imagine · illustrate · inspire

Chitwan Saharia * , William Chan * , Saurabh Saxena † , Lala Li † , Jay Whang † , Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho † , David Fleet † , Mohammad Norouzi *

* Equal contribution. † Core contribution.

Special Thanks

We give thanks to Ben Poole for reviewing our manuscript, early discussions, and providing many helpful comments and suggestions throughout the project. Special thanks to Kathy Meier-Hellstern, Austin Tarango, and Sarah Laszlo for helping us incorporate important responsible AI practices around this project. We appreciate valuable feedback and support from Elizabeth Adkison, Zoubin Ghahramani, Jeff Dean, Yonghui Wu, and Eli Collins. We are grateful to Tom Small for designing the Imagen watermark. We thank Jason Baldridge, Han Zhang, and Kevin Murphy for initial discussions and feedback. We acknowledge hard work and support from Fred Alcober, Hibaq Ali, Marian Croak, Aaron Donsbach, Tulsee Doshi, Toju Duke, Douglas Eck, Jason Freidenfelds, Brian Gabriel, Molly FitzMorris, David Ha, Philip Parham, Laura Pearce, Evan Rapoport, Lauren Skelly, Johnny Soraker, Negar Rostamzadeh, Vijay Vasudevan, Tris Warkentin, Jeremy Weinstein, and Hugh Williams for giving us advice along the project and assisting us with the publication process. We thank Victor Gomes and Erica Moreira for their consistent and critical help with TPU resource allocation. We also give thanks to Shekoofeh Azizi, Harris Chan, Chris A. Lee, and Nick Ma for volunteering a considerable amount of their time for testing out DrawBench. We thank Aditya Ramesh, Prafulla Dhariwal, and Alex Nichol for allowing us to use DALL-E 2 samples and providing us with GLIDE samples. We are thankful to Matthew Johnson and Roy Frostig for starting the JAX project and to the whole JAX team for building such a fantastic system for high-performance machine learning research. Special thanks to Durk Kingma, Jascha Sohl-Dickstein, Lucas Theis and the Toronto Brain team for helpful discussions and spending time Imagening!

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Academic search engines have become the number one resource to turn to in order to find research papers and other scholarly sources. While classic academic databases like Web of Science and Scopus are locked behind paywalls, Google Scholar and others can be accessed free of charge. In order to help you get your research done fast, we have compiled the top list of free academic search engines.

Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.

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BASE is hosted at Bielefeld University in Germany. That is also where its name stems from (Bielefeld Academic Search Engine).

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CORE is an academic search engine dedicated to open-access research papers. For each search result, a link to the full-text PDF or full-text web page is provided.

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Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need anymore to query all those resources separately!

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Semantic Scholar is the new kid on the block. Its mission is to provide more relevant and impactful search results using AI-powered algorithms that find hidden connections and links between research topics.

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Although Baidu Scholar's interface is in Chinese, its index contains research papers in English as well as Chinese.

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RefSeek searches more than one billion documents from academic and organizational websites. Its clean interface makes it especially easy to use for students and new researchers.

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

research paper about google

Google Scholar is an academic search engine, and it is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only let's you find research papers for all academic disciplines for free, but also often provides links to full text PDF file.

Semantic Scholar is a free, AI-powered research tool for scientific literature developed at the Allen Institute for AI. Sematic Scholar was publicly released in 2015 and uses advances in natural language processing to provide summaries for scholarly papers.

BASE , as its name suggest is an academic search engine. It is hosted at Bielefeld University in Germany and that's where it name stems from (Bielefeld Academic Search Engine).

CORE is an academic search engine dedicated to open access research papers. For each search result a link to the full text PDF or full text web page is provided.

Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need any more to query all those resources separately!

research paper about google

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Revealed: the ten research papers that policy documents cite most

  • Dalmeet Singh Chawla 0

Dalmeet Singh Chawla is a freelance science journalist based in London.

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G7 leaders gather for a photo at the Itsukushima Shrine during the G7 Summit in Hiroshima, Japan in 2023

Policymakers often work behind closed doors — but the documents they produce offer clues about the research that influences them. Credit: Stefan Rousseau/Getty

When David Autor co-wrote a paper on how computerization affects job skill demands more than 20 years ago, a journal took 18 months to consider it — only to reject it after review. He went on to submit it to The Quarterly Journal of Economics , which eventually published the work 1 in November 2003.

Autor’s paper is now the third most cited in policy documents worldwide, according to an analysis of data provided exclusively to Nature . It has accumulated around 1,100 citations in policy documents, show figures from the London-based firm Overton (see ‘The most-cited papers in policy’), which maintains a database of more than 12 million policy documents, think-tank papers, white papers and guidelines.

“I thought it was destined to be quite an obscure paper,” recalls Autor, a public-policy scholar and economist at the Massachusetts Institute of Technology in Cambridge. “I’m excited that a lot of people are citing it.”

The most-cited papers in policy

Economics papers dominate the top ten papers that policy documents reference most.

Data from Sage Policy Profiles as of 15 April 2024

The top ten most cited papers in policy documents are dominated by economics research. When economics studies are excluded, a 1997 Nature paper 2 about Earth’s ecosystem services and natural capital is second on the list, with more than 900 policy citations. The paper has also garnered more than 32,000 references from other studies, according to Google Scholar. Other highly cited non-economics studies include works on planetary boundaries, sustainable foods and the future of employment (see ‘Most-cited papers — excluding economics research’).

These lists provide insight into the types of research that politicians pay attention to, but policy citations don’t necessarily imply impact or influence, and Overton’s database has a bias towards documents published in English.

Interdisciplinary impact

Overton usually charges a licence fee to access its citation data. But last year, the firm worked with the London-based publisher Sage to release a free web-based tool that allows any researcher to find out how many times policy documents have cited their papers or mention their names. Overton and Sage said they created the tool, called Sage Policy Profiles, to help researchers to demonstrate the impact or influence their work might be having on policy. This can be useful for researchers during promotion or tenure interviews and in grant applications.

Autor thinks his study stands out because his paper was different from what other economists were writing at the time. It suggested that ‘middle-skill’ work, typically done in offices or factories by people who haven’t attended university, was going to be largely automated, leaving workers with either highly skilled jobs or manual work. “It has stood the test of time,” he says, “and it got people to focus on what I think is the right problem.” That topic is just as relevant today, Autor says, especially with the rise of artificial intelligence.

Most-cited papers — excluding economics research

When economics studies are excluded, the research papers that policy documents most commonly reference cover topics including climate change and nutrition.

Walter Willett, an epidemiologist and food scientist at the Harvard T.H. Chan School of Public Health in Boston, Massachusetts, thinks that interdisciplinary teams are most likely to gain a lot of policy citations. He co-authored a paper on the list of most cited non-economics studies: a 2019 work 3 that was part of a Lancet commission to investigate how to feed the global population a healthy and environmentally sustainable diet by 2050 and has accumulated more than 600 policy citations.

“I think it had an impact because it was clearly a multidisciplinary effort,” says Willett. The work was co-authored by 37 scientists from 17 countries. The team included researchers from disciplines including food science, health metrics, climate change, ecology and evolution and bioethics. “None of us could have done this on our own. It really did require working with people outside our fields.”

Sverker Sörlin, an environmental historian at the KTH Royal Institute of Technology in Stockholm, agrees that papers with a diverse set of authors often attract more policy citations. “It’s the combined effect that is often the key to getting more influence,” he says.

research paper about google

Has your research influenced policy? Use this free tool to check

Sörlin co-authored two papers in the list of top ten non-economics papers. One of those is a 2015 Science paper 4 on planetary boundaries — a concept defining the environmental limits in which humanity can develop and thrive — which has attracted more than 750 policy citations. Sörlin thinks one reason it has been popular is that it’s a sequel to a 2009 Nature paper 5 he co-authored on the same topic, which has been cited by policy documents 575 times.

Although policy citations don’t necessarily imply influence, Willett has seen evidence that his paper is prompting changes in policy. He points to Denmark as an example, noting that the nation is reformatting its dietary guidelines in line with the study’s recommendations. “I certainly can’t say that this document is the only thing that’s changing their guidelines,” he says. But “this gave it the support and credibility that allowed them to go forward”.

Broad brush

Peter Gluckman, who was the chief science adviser to the prime minister of New Zealand between 2009 and 2018, is not surprised by the lists. He expects policymakers to refer to broad-brush papers rather than those reporting on incremental advances in a field.

Gluckman, a paediatrician and biomedical scientist at the University of Auckland in New Zealand, notes that it’s important to consider the context in which papers are being cited, because studies reporting controversial findings sometimes attract many citations. He also warns that the list is probably not comprehensive: many policy papers are not easily accessible to tools such as Overton, which uses text mining to compile data, and so will not be included in the database.

research paper about google

The top 100 papers

“The thing that worries me most is the age of the papers that are involved,” Gluckman says. “Does that tell us something about just the way the analysis is done or that relatively few papers get heavily used in policymaking?”

Gluckman says it’s strange that some recent work on climate change, food security, social cohesion and similar areas hasn’t made it to the non-economics list. “Maybe it’s just because they’re not being referred to,” he says, or perhaps that work is cited, in turn, in the broad-scope papers that are most heavily referenced in policy documents.

As for Sage Policy Profiles, Gluckman says it’s always useful to get an idea of which studies are attracting attention from policymakers, but he notes that studies often take years to influence policy. “Yet the average academic is trying to make a claim here and now that their current work is having an impact,” he adds. “So there’s a disconnect there.”

Willett thinks policy citations are probably more important than scholarly citations in other papers. “In the end, we don’t want this to just sit on an academic shelf.”

doi: https://doi.org/10.1038/d41586-024-00660-1

Autor, D. H., Levy, F. & Murnane, R. J. Q. J. Econ. 118 , 1279–1333 (2003).

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Costanza, R. et al. Nature 387 , 253–260 (1997).

Willett, W. et al. Lancet 393 , 447–492 (2019).

Article   PubMed   Google Scholar  

Steffen, W. et al. Science 347 , 1259855 (2015).

Rockström, J. et al. Nature 461 , 472–475 (2009).

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    Google publishes hundreds of research papers each year. Publishing is important to us; it enables us to collaborate and share ideas with, as well as learn from, the broader scientific community. Submissions are often made stronger by the fact that ideas have been tested through real product implementation by the time of publication.

  5. Google Research

    The research we do today becomes the Google of the future. Google itself began with a research paper, published in 1998, and was the foundation of Google Search. Our ongoing research over the past 25 years has transformed not only the company, but how people are able to interact with the world and its information.

  6. PDF The Anatomy of a Search Engine

    The Anatomy of a Large-Scale Hypertextual Web Search Engine. Sergey Brin and Lawrence Page Computer Science Department, Stanford University, Stanford, CA 94305, USA [email protected] and [email protected] Abstract In this paper, we present Google, a prototype of a large-scale search engine which makes heavy use of the structure present ...

  7. PDF Google's Hybrid Approach to Research

    Google's Hybrid Approach to Research Alfred Spector Google Inc. [email protected] Peter Norvig Google Inc. [email protected] Slav Petrov Google Inc. [email protected] 1 Introduction In this paper, we describe how we organize Computer Science (CS) research at Google. We focus on how we integrate research and development (R&D) and discuss the ...

  8. About Google Scholar

    Google Scholar provides a simple way to broadly search for scholarly literature. From one place, you can search across many disciplines and sources: articles, theses, books, abstracts and court ...

  9. 18 Google Scholar tips all students should know

    The comprehensive database of research papers, legal cases and other scholarly publications was the fourth Search service Google launched, Anurag says. In honor of this very important tool's 18th anniversary, I asked Anurag to share 18 things you can do in Google Scholar that you might have missed. 1.

  10. Machine Intelligence

    Machine Intelligence. Google is at the forefront of innovation in Machine Intelligence, with active research exploring virtually all aspects of machine learning, including deep learning and more classical algorithms. Exploring theory as well as application, much of our work on language, speech, translation, visual processing, ranking and ...

  11. Research

    Our teams aspire to make discoveries that positively impact society. Core to our approach is sharing our research and tools to fuel progress in the field, to help more people more quickly. We regularly publish in academic journals, release projects as open source, and apply research to Google products to benefit users at scale. Learn more about ...

  12. How to use Google Scholar: the ultimate guide

    Google Scholar searches are not case sensitive. 2. Use keywords instead of full sentences. 3. Use quotes to search for an exact match. 3. Add the year to the search phrase to get articles published in a particular year. 4. Use the side bar controls to adjust your search result.

  13. PDF An overview of Bard: an early experiment with generative AI

    An overview of Bard: an early experiment with generative AI James Manyika, SVP, Research, Technology and Society, and Sissie Hsiao, Vice President and General Manager, Google Assistant and Bard Editor's note: This is a living document and will be updated periodically as we continue to rapidly improve Bard's capabilities as well as

  14. PDF MapReduce: Simplied Data Processing on Large Clusters

    in the paper. Programs written in this functional style are automati-cally parallelized and executed on a large cluster of com-modity machines. The run-time system takes care of the details of partitioning the input data, scheduling the pro-gram's execution across a set of machines, handling ma-chine failures, and managing the required inter ...

  15. PDF Spanner: Google's Globally-Distributed Database

    Google, Inc. Abstract Spanner is Google's scalable, multi-version, globally-distributed, and synchronously-replicated database. It is the first system to distribute data at global scale and sup-port externally-consistent distributed transactions. This paper describes how Spanner is structured, its feature set,

  16. Google Scholar Search Help

    Get the most out of Google Scholar with some helpful tips on searches, email alerts, citation export, and more. Finding recent papers. Your search results are normally sorted by relevance, not by date. To find newer articles, try the following options in the left sidebar: click "Since Year" to show only recently published papers, sorted by ...

  17. Google Scholar reveals its most influential papers for 2020

    The journal, Nucleic Acids Research, while ranked outside the top 10 of Google Scholar's most influential journals, has more papers with 3,000+ citations each than The Lancet (ranked 4th). 7.

  18. PDF PaLM 2 Technical Report

    PaLM 2 Technical Report. PaLM 2 Technical Report. Google* Abstract We introduce PaLM 2, a new state-of-the-art language model that has better multilingual and reasoning capabilities and is more compute-efficient than its predecessor PaLM. PaLM 2 is a Transformer-based model trained using a mixture of objectives.

  19. Google Scholar reveals its most influential papers for 2021

    The five-year-old paper's astonishing ascendancy continues, from 25,256 citations in 2019 to 49,301 citations in 2020 to 82,588 citations in 2021. We wrote about it last year here. The 2021 ...

  20. Imagen: Text-to-Image Diffusion Models

    Google Research, Brain Team. We present Imagen, a text-to-image diffusion model with an unprecedented degree of photorealism and a deep level of language understanding. Imagen builds on the power of large transformer language models in understanding text and hinges on the strength of diffusion models in high-fidelity image generation.

  21. Attention Is All You Need

    An illustration of main components of the transformer model from the paper "Attention Is All You Need" is a landmark 2017 research paper by Google. Authored by eight scientists, it was responsible for expanding 2014 attention mechanisms proposed by Bahdanau et al. into a new deep learning architecture known as the transformer.The paper is considered by some to be a founding document for modern ...

  22. The best academic search engines [Update 2024]

    Get 30 days free. 1. Google Scholar. Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.

  23. PDF The Google File System

    The aggregate read rate reaches 94 MB/s, about 75% of the 125 MB/s linklimit, for 16 readers, or 6 MB/s per client. The efficiency drops from 80% to 75% because as the number of readers increases, so does the probability that multiple readers simultaneously read from the same chunkserver.

  24. MapReduce: Simplified Data Processing on Large Clusters

    MapReduce is a programming model and an associated implementation for processing and generating large data sets. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Many real world ...

  25. This paper from Google DeepMind Provides an Overview of Synthetic Data

    In the rapidly evolving landscape of artificial intelligence (AI), the quest for large, diverse, and high-quality datasets represents a significant hurdle. Synthetic data has been identified as a pivotal solution to this challenge, promising to bridge the gap caused by data scarcity, privacy issues, and the high costs associated with data acquisition. This artificial data, crafted through ...

  26. Google's new technique gives LLMs infinite context

    A new paper by researchers at Google claims to give large language models (LLMs) the ability to work with text of infinite length. The paper introduces Infini-attention, a technique that ...

  27. [2404.07143] Leave No Context Behind: Efficient Infinite Context

    This work introduces an efficient method to scale Transformer-based Large Language Models (LLMs) to infinitely long inputs with bounded memory and computation. A key component in our proposed approach is a new attention technique dubbed Infini-attention. The Infini-attention incorporates a compressive memory into the vanilla attention mechanism and builds in both masked local attention and ...

  28. Revealed: the ten research papers that policy documents cite most

    The top ten most cited papers in policy documents are dominated by economics research. When economics studies are excluded, a 1997 Nature paper 2 about Earth's ecosystem services and natural ...

  29. Fall 2024 CSCI Special Topics Courses

    CSCI 5980 Cloud ComputingMeeting Time: 09:45 AM‑11:00 AM TTh Instructor: Ali AnwarCourse Description: Cloud computing serves many large-scale applications ranging from search engines like Google to social networking websites like Facebook to online stores like Amazon. More recently, cloud computing has emerged as an essential technology to enable emerging fields such as Artificial ...