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Scopus Search

Scopus quickly delivers the information you're looking for from over 92m records. Updated daily, Scopus features state-of-the-art search tools and filters to empower research efficiency.

Increase research efficiency

Having access to comprehensive content and high-quality data is only effective if you can easily find the information you need. Uncovering trends, discovering sources and potential collaborators, and building deeper insights require effective search tools that can identify the right results.

Identify trends for key topics

Scopus’ literature search is built to distill massive amounts of information down to the most relevant documents and information in less time.

With Scopus you can search and filter results in the following ways:

Document search : Search directly from the homepage and use detailed search options to ensure you find the document(s) you want

Author search : Search for a specific author by name or by Open Research and Contributor Identifier ID (ORCID)

Affiliation search : Identify and assess an affiliation’s scholarly output, collaborating institutions and top authors

Advanced search : Narrow the scope of your search using field codes, proximity operators and/or Boolean operators

Refine results : Scopus makes it easy to refine your results list to specific categories of documents

Language interface : The Scopus interface is available in Chinese and Japanese; content is not localized, but you can switch the interface to one of these language options (and switch back to English, the default language) at the bottom of any Scopus page

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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."

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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)

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The Directory of Open Access Journals

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Doaj in numbers.

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DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, and is committed to ensuring quality content is freely available online for everyone.

DOAJ is committed to keeping its services free of charge, including being indexed, and its data freely available.

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PubMed® comprises more than 37 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full text content from PubMed Central and publisher web sites.

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Study reveals a cell-eat-cell world.

From normal vertebrate development to tumor cell cannibalism, cell-in-cell events occur in many different contexts across the tree of life

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Do cats experience grief? New research suggests they might

Researchers from Oakland University surveyed hundreds of cat caregivers and found that cats exhibited behaviors associated with grief after a fellow cat or dog in the household died.

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Genetic mutations affect nearly all human diseases. Some genetic disorders such as cystic fibrosis are caused by mutations in a single gene that a person inherits from their parents. Other diseases can be caused by changes in multiple genes or from a combination of gene mutations and environmental factors. We still have a lot to […]

Updated Genomes Terminology! “Representative Genome” is Replaced with “Reference Genome”

NCBI is streamlining the terminology around our reference genomes. We currently have a small set of genomes collectively called representatives and an even smaller set called references. We have slowly converged on the term reference to refer to both sets.   A genome is labeled reference if it is deemed to be the best available genome … Continue reading Updated Genomes Terminology! “Representative Genome” is Replaced with “Reference Genome” →

Welcoming Senator Reed and Congressional Staff to the NIH Campus

On September 13, I was delighted to welcome Senator Jack Reed to the NIH campus. His tour included a visit to the NIH Clinical Center, where he heard about recent findings in RNA sequencing from experts from the National Institute of Environmental Health Sciences and the National Human Genome Research Institute. We then joined several senior leaders and scientists from the National Cancer Institute to discuss advances in childhood cancer research, and to visit a pediatric oncology lab and meet with a patient who received treatment there.

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Research articles

Impurity-healing interface engineering for efficient perovskite submodules.

• Haifei Wang
• Shuojian Su

H5N1 clade 2.3.4.4b dynamics in experimentally infected calves and cows

• Nico Joel Halwe
• Konner Cool
• Juergen A. Richt

The evolution of private reputations in information-abundant landscapes

In an information-abundant landscape, people can accurately judge the reputations of others by researching only a fraction of the available information while forgiving some instances of bad behaviour.

• Sebastián Michel-Mata
• Mari Kawakatsu
• Corina E. Tarnita

Forest fire size amplifies postfire land surface warming

Climate warming has increased forest fire sizes, amplifying postfire summer warming, with broadleaf trees mitigating this effect; climate-smart forestry should increase broadleaf tree cover to manage future fire risks.

• Sebastiaan Luyssaert

Future increase in extreme El Niño supported by past glacial changes

A combination of palaeoclimate proxies and simulations shows that a common mechanism controls El Niño variation in cold and warm states, which supports expectations of more extreme El Niño occurrence in the future.

• Kaustubh Thirumalai
• Pedro N. DiNezio
• Allison Jacobel

Intragenic DNA inversions expand bacterial coding capacity

Reversible DNA inversions found entirely within genes enable increased coding capacity by encoding multiple versions of a protein in bacteria and archaea.

• Rachael B. Chanin
• Patrick T. West
• Ami S. Bhatt

Transferrin receptor targeting chimeras for membrane protein degradation

Transferrin receptor targeting chimeras have been developed that enable targeting of drug resistance in epidermal growth factor receptor-driven lung cancer and reversible control of human primary chimeric antigen receptor T cells, representing a promising new family of bifunctional antibodies for targeted cancer therapy.

• Dingpeng Zhang
• Jhoely Duque-Jimenez

The genetic architecture of protein stability

By experimentally sampling from sequence spaces larger than 10 10 and using thermodynamic models, the genetic structure of at least some proteins can be well described, indicating that protein genetics is simpler than anticipated.

• Andre J. Faure
• Aina Martí-Aranda

Larger and more instructable language models become less reliable

Scaling up and shaping up large language models increased their tendency to provide sensible yet incorrect answers at difficulty levels humans cannot supervise, highlighting the need for a fundamental shift in artificial intelligence design towards reliability.

• Wout Schellaert
• José Hernández-Orallo

Human hippocampal and entorhinal neurons encode the temporal structure of experience

Single-neuron recordings from intracranial electrodes inserted into human brains for clinical reasons suggest that the temporal structure of human experience is encoded in human hippocampal and entorhinal neurons.

• Pawel Tacikowski
• Güldamla Kalender
• Itzhak Fried

Jet stream controls on European climate and agriculture since 1300 ce

Tree-ring records used to reconstruct the variability of the European jet stream from 1300 to 2004 ce show modulation of extreme regional climate events and extensive impacts on agriculture and human well-being.

• Ellie Broadman
• Valerie Trouet

AARS1 and AARS2 sense l -lactate to regulate cGAS as global lysine lactyltransferases

The tRNA synthases AARS1 and AARS2 are identified as evolutionarily conserved sensors of intracellular l -lactate to mediate the global lysine lactylome.

Microbial iron limitation in the ocean’s twilight zone

The distribution and uptake of siderophores across a meridional section of the eastern Pacific Ocean suggests that iron availability limits microbial metabolism in the upper mesopelagic in several large ocean basins.

• Jingxuan Li
• Lydia Babcock-Adams
• Daniel J. Repeta

Brazilian fossils reveal homoplasy in the oldest mammalian jaw joint

The dentary–squamosal contact, traditionally considered to be a typical mammalian feature, evolved more than once and is more evolutionary labile than previously considered.

• James R. G. Rawson
• Agustín G. Martinelli
• Emily J. Rayfield

Designed endocytosis-inducing proteins degrade targets and amplify signals

Computationally designed genetically encoded proteins can be used to target surface proteins, thereby triggering endocytosis and subsequent intracellular degradation, activating signalling or increasing cellular uptake in specific tissues.

• Buwei Huang
• Mohamad Abedi
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Bendable non-silicon RISC-V microprocessor

Flex-RV, a 32-bit microprocessor based on an open RISC-V instruction set fabricated with indium gallium zinc oxide thin-film transistors on a flexible polyimide substrate, enables an ultralow-cost bendable and flexible microprocessor.

• Jedrzej Kufel
• Vijay Janapa Reddi

Using both faces of polar semiconductor wafers for functional devices

A new approach is described for fabricating devices on each of the faces of the same gallium nitride semiconductor wafer, using the cation face for photonic devices and the anion face for electronic devices.

• Len van Deurzen
• Eungkyun Kim
• Henryk Turski

The type 2 cytokine Fc–IL-4 revitalizes exhausted CD8 + T cells against cancer

Fc–IL-4, a typical type 2 cytokine, reinvigorates exhausted CD8 + T cells in tumours, underscoring this fusion protein as a potent immunotherapy that synergizes effectively with type 1 immunity against cancer.

• Zhiliang Bai

Nitrogen-doped amorphous monolayer carbon

Free-standing nitrogen-doped amorphous monolayer carbon consisting of mixed five-, six- and seven-membered rings was prepared through the polymerization of pyrrole within the confined interlayer cavity of a removable layered-double-hydroxide template.

Phages reconstitute NAD + to counter bacterial immunity

A study shows that many phages are capable of evading antiphage defence systems of bacteria by reconstituting NAD + from its degradation products in infected cells.

• Ilya Osterman
• Hadar Samra
• Rotem Sorek

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Cultural Remittances and Modern Fertility

We argue that migrants played a significant role in the diffusion of the demographic transition from France to the rest of Europe in the late 19th century. Employing novel data on French immigration from other European regions from 1850 to 1930, we find that higher immigration to France translated into lower fertility in the region of origin after a few decades - both in cross-region regressions for various periods, and in a panel setting with region fixed effects. These results are robust to the inclusion of a variety of controls, and across multiple specifications. We also find that immigrants who themselves became French citizens achieved lower fertility, particularly those who moved to French regions with the lowest fertility levels. We interpret these findings in terms of cultural remittances, consistently with insights from a theoretical framework where migrants act as vectors of cultural diffusion, spreading new information, social norms and preferences pertaining to modern fertility to their regions of origin.

We thank Guillaume Blanc, Guillaume Daudin and Casper Worm Hansen for excellent conference discussions. We thank seminar and conference participants at Panthéon-Assas University, the Paris School of Economics, Uppsala University, the University of Manchester, Lund University, UC Riverside, the California Center for Population Research at UCLA, Duke University, San Diego State University, Brown University, PUC-Rio, EIEF, CRETE in Milos, Universitat Autònoma de Barcelona, University of Luxembourg, Barcelona Summer Forum, Tel-Aviv University, AMSE, Bocconi, IESEG and University of Milan. We also thank Anne-Sophie Bruno, David de la Croix, Petros Milionis, Martín Fernández-Sánchez, James Fenske, Martin Fiszbein, Tomás Guanziroli, Torsten Persson, Thomas Piketty, and Katia Zhuravskaya, for useful comments. We also thank Enjie Jack Ma, Maximilian Doerfler, and Mael Astruc-Le Souder for excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Knowledge grows step-by-step despite the exponential growth of papers, finds study

Scientific knowledge is growing at a linear rate despite an exponential increase in publications. That’s according to a study by physicists in China and the US, who say their finding points to a decline in overall scientific productivity. The study therefore contradicts the notion that productivity and knowledge grow hand in hand – but adds weight to the view that the rate of scientific discovery may be slowing or that “information fatigue” and the vast number of papers can drown out new discoveries .

Defining knowledge is complex, but it can be thought of as a network of interconnected beliefs and information. To measure it, the authors previously created a knowledge quantification index (KQI). This tool uses various scientific impact metrics to examine the network structures created by publications and their citations and quantifies how well publications reduce the uncertainty of the network, and thus knowledge.

The researchers claim the tool’s effectiveness has been validated through multiple approaches, including analysing the impact of work by Nobel laureates.

In the latest study, published on arXiv , the team analysed 213 million scientific papers, published between 1800 and 2020, as well as 7.6 million patents filed between 1976 and 2020. Using the data, they built annual snapshots of citation networks, which they then scrutinised with the KQI to observe changes in knowledge over time.

The researchers – based at Shanghai Jiao Tong University in Shanghai, the University of Minnesota in the US and the Institute of Geographic Sciences and Natural Resources Research in Beijing –found that while the number of publications has been increasing exponentially, knowledge has not.

Instead, their KQI suggests that knowledge has been growing in a linear fashion. Different scientific disciplines do display varying rates of knowledge growth, but they all have the same linear growth pattern. Patent growth was found to be much slower than publication growth but also shows the linear growth in the KQI.

‘Hidden’ citations conceal the true impact of scientific research

According to the authors, the analysis indicates “no significant change in the rate of human knowledge acquisition”, suggesting that our understanding of the world has been progressing at a steady pace.

If scientific productivity is defined as the number of papers required to grow knowledge, this signals a significant decline in productivity, the authors claim.

The analysis also revealed inflection points associated with new discoveries, major breakthroughs and other important developments, with knowledge growing at different linear rates before and after.

Such inflection points create the illusion of exponential knowledge growth due to the sudden alteration in growth rates, which may, according to the study authors, have led previous studies to conclude that knowledge is growing exponentially.

Research focus

“Research has shown that the disruptiveness of individual publications – a rough indicator of knowledge growth – has been declining over recent decades,” says Xiangyi Meng , a physicist at Northwestern University in the US, who works in network science but was not involved in the research. “This suggests that the rate of knowledge growth must be slower than the exponential rise in the number of publications.”

Meng adds, however, that the linear growth finding is “surprising” and “somewhat pessimistic” – and that further analysis is needed to confirm if knowledge growth is indeed linear or whether it “more likely, follows a near-linear polynomial pattern, considering that human civilization is accelerating on a much larger scale”.

Due to the significant variation in the quality of scientific publications, Meng says that article growth may “not be a reliable denominator for measuring scientific efficiency”. Instead, he suggests that analysing research funding and how it is allocated and evolves over time might be a better focus.

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AMRC briefing paper on embedding research in the NHS

On 19 September 2024 the Association of Medical Research Charities (AMRC) published a briefing paper on embedding research in the NHS .

The briefing outlined why research and innovation must be a central part of the solution in the NHS 10-year health plan, and how we can ensure that research is embedded effectively in the NHS by prioritising three areas:

• supporting a thriving clinical research workforce
• maximising opportunities for everyone to take part in research
• making it easy to deliver research throughout the NHS.

We welcome the briefing from AMRC and our Director of Approvals Service, Janet Messer has responded below.

“We were pleased to see the helpful briefing from AMRC following on from the publication of Lord Darzi’s review last week. It provides a further reminder of the importance of research in the NHS. “We agree that charities play a vital role in health and social care research and the AMRC briefing highlights the wide range of benefits non-commercially funded research brings to UK. “The briefing highlights three priorities to ensure research is embedded effectively in the NHS and the Health Research Authority is already working with our partners to support work in these key areas. “We are pleased to see that the HRA’s work with others to champion the importance of diversity and inclusion in research has been recognised. The UK’s diverse population, alongside the well-established research infrastructure in the NHS, provides a unique opportunity for properly representative research to be carried out. This is a key way to tackling health inequalities and to support this we will soon be asking for feedback on our draft inclusion and diversity plan and guidance which is designed to support the research community to design inclusive research. “We are also working with others to clarify how data can be used to identify and invite people to take part in research, to help increase recruitment to clinical studies and trials. “Our aim is to make it easy to do research that people can trust. This briefing makes it clear that more needs to be done to make it easier to deliver research in the NHS, and we are committed to doing everything we can to support this. We are working with others on a range of actions to speed up the set-up of research in the NHS. Across the NHS we have already made a difference to the set-up of commercial research through the National Contract Value Review (NCVR) process which removes the duplication in costing by individual NHS organisations. Thanks to NCVR in 2023 we saw that participating commercial study set-up times were over 100 days quicker compared to pre-pandemic levels. “We understand that the research community is keen to know about the upcoming changes to Clinical Trials Legislation and we have committed to ensuring that we share guidance well in advance of any changes coming into effect so that everyone understands what they need to do.”

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Nnscaler: exploring a new paradigm for parallel execution in deep learning, share this page.

Author: Youshan Miao

Today, deep learning has permeated our daily lives. As the size of models continues to grow, training these models on massive GPU accelerators has become increasingly time-consuming and costly. To effectively harness the power of massive GPUs and enhance efficiency, researchers have been developing various parallel strategies to improve performance across multiple devices. However, many potentially efficient parallel strategies remain unexplored. Fully exploring these possibilities to further unlock performance remains a major challenge in both research and application.

Recently, researchers from Microsoft Research Asia proposed nnScaler, a framework that supports freely expressing parallel strategies through a set of parallel primitives while minimizing search costs by utilizing a strategy-constrained search space.

Parallel primitives: A unified framework to describe parallel strategies

Mainstream training systems, such as Megatron-LM, DeepSpeed, and Alpa, typically incorporate built-in parallel strategies like data-parallelism, tensor-parallelism, and pipeline-parallelism, which can be combined through configuration. While this approach is efficient for most cases and convenient for users, it may overlook more efficient strategies. Including new efficient parallel strategies often require substantial modifications to the underlying system code, which is impractical.

Therefore, researchers revisited the fundamental components of parallel strategies. The execution of deep learning models can usually be represented as a data-flow graph, where tensors (representing data) are the edges, and tensor operators are the vertices. The process of parallelization involves transforming the computation data-flow graph, originally designed for single-device execution, into a distributed data-flow graph for multi-device execution. Thus, researchers propose a set of basic operations as parallel primitives, including:

• op-trans : Describes how operators and tensors are partitioned.
• op-assign : Assigns the partitioned operators to specific devices.
• op-order : Specifies the execution order of operators on the same device.

By utilizing these primitives, we can precisely describe how each operator and tensor in the data-flow graph is partitioned and scheduled across devices (spatially) and over time (temporal order on the same device).

These parallel primitives can naturally express various widely used parallel strategies. For instance, data-parallelism can be expressed as partitioning all forward pass and backward pass operators along the data sample dimension and distributing them evenly across all devices, while copying the optimizer operators to each device. All operators on each device maintain the same execution order as in the original graph. The introduction of parallel primitives allows for the flexible description and integration of various parallel strategies within a unified framework, significantly expanding the representational scope of parallel strategy spaces.

This universality not only systematically expresses existing parallel strategies but also provides the potential to explore new ones. For example, for operators that produce intermediate results too large for a single device, the original strategy might be tensor-parallelism with communication coordination. However, using parallel primitives, we can partition the tensor for that specific operator and schedule all partitions on the same device for sequential execution, successfully executing the operation while avoiding communication overhead, as shown in the figure below.

Enhancing efficiency through expert-guided strategy search

While parallel primitives expand the strategy space, this expansion also introduces a new challenge—the vast strategy space makes it difficult to complete searches within a limited time. With a multitude of possible combinations, efficiently finding the optimal strategy becomes a pressing issue.

nnScalerleverages domain expert wisdom to guide effective strategy searches. This guidance can be described through parallel primitives, seamlessly integrating into the system. For example, as shown in the figure below, researchers can constrain the operator’s partitioning scheme to the options specified in the algo set and limit the partitioning to the number of pieces specified by num.

By setting specific constraints, experts can significantly narrow the search space, making the search process more efficient and targeted. Experiments have shown  up to 10x increase in search efficiency without compromising the effectiveness of the strategies.

This approach can uncover high-performance strategies that existing methods overlook and complete searches in a shorter time, thereby improving the efficiency of deep learning training. nnScaler has been validated in the training of multiple deep learning models, demonstrating significant performance improvements.

For more details, please refer to the nnScaler paper: https://www.usenix.org/conference/osdi24/presentation/lin-zhiqi (opens in new tab)

By introducing parallel primitives and expert-guided strategy searches, nnScaler has effectively addressed many issues in the design of parallel strategies for deep learning. This method not only significantly expands the space of parallel strategies, but also provides new directions and tools for future research in parallel strategies. Researchers are eager to see this method demonstrate its potential in broader applications, bringing more possibilities to the development of deep learning.

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Computer Science > Computation and Language

Title: towards a realistic long-term benchmark for open-web research agents.

Abstract: We present initial results of a forthcoming benchmark for evaluating LLM agents on white-collar tasks of economic value. We evaluate agents on real-world "messy" open-web research tasks of the type that are routine in finance and consulting. In doing so, we lay the groundwork for an LLM agent evaluation suite where good performance directly corresponds to a large economic and societal impact. We built and tested several agent architectures with o1-preview, GPT-4o, Claude-3.5 Sonnet, Llama 3.1 (405b), and GPT-4o-mini. On average, LLM agents powered by Claude-3.5 Sonnet and o1-preview substantially outperformed agents using GPT-4o, with agents based on Llama 3.1 (405b) and GPT-4o-mini lagging noticeably behind. Across LLMs, a ReAct architecture with the ability to delegate subtasks to subagents performed best. In addition to quantitative evaluations, we qualitatively assessed the performance of the LLM agents by inspecting their traces and reflecting on their observations. Our evaluation represents the first in-depth assessment of agents' abilities to conduct challenging, economically valuable analyst-style research on the real open web.

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