Semantic Scholar

Research papers, paper citations and author metrics

Semantic Scholar returns paper and citation search, paper abstracts, summaries, authors and influence, plus author metrics and up to 10 top-cited papers; dates, summaries, PDFs and affiliation matches may be unavailable.

Get author

Get a Semantic Scholar author’s impact metrics and up to 10 most-cited papers from their name. When an institution is provided, only listed affiliations can be matched; authors without a listed affiliation cannot match.

Your information

Author

Researcher name, for example Fei-Fei Li.

More options

InstitutionOptional

Institution to match against listed affiliations, for example Southwest Petroleum University.

1 credit per run

Example results

Name: Yoshua Bengio
H Index: 212
Homepage: Not provided
Author ID: 1751762
Total Citations: 574,497
Author Page Link: semanticscholar.org
Number of Papers: 811
Top Papers: Top Papers
Title Year Venue Citations Paper Link
Gradient-based learning applied to document recognition
1998
Proceedings of the IEEE
62,855
semanticscholar.org
Deep Learning
2015
—
38,310
semanticscholar.org
Neural Machine Translation by Jointly Learning to Align and Translate
2014
International Conference on Learning Representations
30,076
semanticscholar.org
Graph Attention Networks
2017
International Conference on Learning Representations
28,556
semanticscholar.org
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
2014
Conference on Empirical Methods in Natural Language Processing
27,619
semanticscholar.org
Understanding the difficulty of training deep feedforward neural networks
2010
International Conference on Artificial Intelligence and Statistics
19,674
semanticscholar.org
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling
2014
arXiv.org
15,130
semanticscholar.org
Representation Learning: A Review and New Perspectives
2012
IEEE Transactions on Pattern Analysis and Machine Intelligence
14,336
semanticscholar.org
Random Search for Hyper-Parameter Optimization
2012
Journal of machine learning research
11,660
semanticscholar.org
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
2015
International Conference on Machine Learning
10,945
semanticscholar.org
Affiliations: None

Top Papers
Title	Year	Venue	Citations	Paper Link
Gradient-based learning applied to document recognition	1998	Proceedings of the IEEE	62,855	semanticscholar.org
Deep Learning	2015	—	38,310	semanticscholar.org
Neural Machine Translation by Jointly Learning to Align and Translate	2014	International Conference on Learning Representations	30,076	semanticscholar.org
Graph Attention Networks	2017	International Conference on Learning Representations	28,556	semanticscholar.org
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation	2014	Conference on Empirical Methods in Natural Language Processing	27,619	semanticscholar.org
Understanding the difficulty of training deep feedforward neural networks	2010	International Conference on Artificial Intelligence and Statistics	19,674	semanticscholar.org
Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling	2014	arXiv.org	15,130	semanticscholar.org
Representation Learning: A Review and New Perspectives	2012	IEEE Transactions on Pattern Analysis and Machine Intelligence	14,336	semanticscholar.org
Random Search for Hyper-Parameter Optimization	2012	Journal of machine learning research	11,660	semanticscholar.org
Show, Attend and Tell: Neural Image Caption Generation with Visual Attention	2015	International Conference on Machine Learning	10,945	semanticscholar.org

Example data · Run in Studio for fresh results.

About Semantic Scholar

Semantic Scholar (S2) Search papers finds relevant studies by topic or title words, with optional field, year, and access filters.

Get paper returns a paper’s abstract, summary, publication details, and citation influence from its title, DOI, or Semantic Scholar link.

Get author returns impact metrics and up to 10 most-cited papers from a researcher name, with an optional institution to match listed affiliations.

Built by Fous from semanticscholar.org and checked automatically; it last passed a check on Sep 29, 2026. Fous is not affiliated with Semantic Scholar.

Actions

Get author

1 credit per run

What you provide

Field	Type	Required	Description
Author`author`	Text	Required	Researcher name, for example Fei-Fei Li.Example: Yoshua Bengio
Institution`institution`	Text	Optional	Institution to match against listed affiliations, for example Southwest Petroleum University.Example: Southwest Petroleum University

What you get

Field	Type	Description
Name`name`	Text	Researcher name shown on Semantic Scholar.Example: Yoshua Bengio
H Index`h_index`	Number	Author h-index.Example: 212
Homepage`homepage`	Text	Researcher homepage, if listed.Example: https://scholar.google.com/citations?user=rDfyQnIAAAAJ&hl=en
Author ID`author_id`	Text	Semantic Scholar author ID.Example: 1751762
Top Papers`top_papers`	List	Up to 10 most-cited publications, from highest to lowest citation count.
Year`top_papers[].year`	Number	Example: 1998
Title`top_papers[].title`	Text	Example: Gradient-based learning applied to document recognition
Venue`top_papers[].venue`	Text	Example: Proceedings of the IEEE
Citations`top_papers[].citations`	Number	Example: 62855
Paper Link`top_papers[].paper_link`	Text	Example: https://www.semanticscholar.org/paper/162d958ff885f1462aeda91cd72582323fd6a1f4
Affiliations`affiliations`	List	Listed institutions, or an empty list when none are listed.
Total Citations`total_citations`	Number	Total Semantic Scholar citations.Example: 574497
Author Page Link`author_page_link`	Text	Researcher page on Semantic Scholar.Example: https://www.semanticscholar.org/author/1751762
Number of Papers`number_of_papers`	Number	Number of papers attributed to this author.Example: 811

Example result

For Author: Yoshua Bengio

JSON

{
  "name": "Yoshua Bengio",
  "h_index": 212,
  "homepage": null,
  "author_id": "1751762",
  "top_papers": [
    {
      "year": 1998,
      "title": "Gradient-based learning applied to document recognition",
      "venue": "Proceedings of the IEEE",
      "citations": 62855,
      "paper_link": "https://www.semanticscholar.org/paper/162d958ff885f1462aeda91cd72582323fd6a1f4"
    },
    {
      "year": 2015,
      "title": "Deep Learning",
      "venue": null,
      "citations": 38310,
      "paper_link": "https://www.semanticscholar.org/paper/2913c2bf3f92b5ae369400a42b2d27cc5bc05ecb"
    },
    {
      "year": 2014,
      "title": "Neural Machine Translation by Jointly Learning to Align and Translate",
      "venue": "International Conference on Learning Representations",
      "citations": 30076,
      "paper_link": "https://www.semanticscholar.org/paper/fa72afa9b2cbc8f0d7b05d52548906610ffbb9c5"
    }
  ],
  "affiliations": [],
  "total_citations": 574497,
  "author_page_link": "https://www.semanticscholar.org/author/1751762",
  "number_of_papers": 811
}

Get paper

1 credit per run

Get a paper’s abstract, short summary, authors, publication details, and citation influence from its title, DOI, or Semantic Scholar link. Some papers lack a publication date, summary, or free PDF.

What you provide

Field	Type	Required	Description
Paper`paper`	Text	Required	Paper title, DOI, or Semantic Scholar paper link; for example, BERT: Pre-training of Deep Bidirectional Transformers.Example: https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776

What you get

Field	Type	Description
DOI`doi`	Text	Digital object identifier.Example: 10.18653/v1/N19-1423
Tldr`tldr`	Text	One-sentence paper summary.Example: A new simple network architecture, the Transformer, based solely on attention…
Year`year`	Number	Publication year.Example: 2017
Title`title`	Text	Paper title.Example: Attention is All you Need
Venue`venue`	Text	Publication venue.Example: Neural Information Processing Systems
Authors`authors`	List	Author names.
Abstract`abstract`	Text	Paper abstract.
Paper Link`paper_link`	Text	Semantic Scholar paper page.Example: https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776
Free PDF Link`free_pdf_link`	Text	Link to a free PDF, if available.Example: https://arxiv.org/pdf/1706.03762.pdf
Citation Count`citation_count`	Number	Number of citations.Example: 194179
Fields of Study`fields_of_study`	List	Fields of study.
Reference Count`reference_count`	Number	Number of references.Example: 41
Publication Date`publication_date`	Text	Publication date (YYYY-MM-DD).Example: 2017-06-12
Semantic Scholar Paper ID`semantic_scholar_paper_id`	Text	Semantic Scholar paper ID.Example: 204e3073870fae3d05bcbc2f6a8e263d9b72e776
Influential Citation Count`influential_citation_count`	Number	Number of influential citations.Example: 20803

Example result

For Paper: https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776

JSON

{
  "doi": null,
  "tldr": "A new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely is proposed, which generalizes well to other tasks by app…",
  "year": 2017,
  "title": "Attention is All you Need",
  "venue": "Neural Information Processing Systems",
  "authors": [
    "Ashish Vaswani",
    "Noam Shazeer",
    "Niki Parmar"
  ],
  "abstract": "The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration. The best performing models also connect the encoder and d…",
  "paper_link": "https://www.semanticscholar.org/paper/204e3073870fae3d05bcbc2f6a8e263d9b72e776",
  "free_pdf_link": "https://arxiv.org/pdf/1706.03762.pdf",
  "citation_count": 194179,
  "fields_of_study": [
    "Computer Science"
  ],
  "reference_count": 41,
  "publication_date": "2017-06-12",
  "semantic_scholar_paper_id": "204e3073870fae3d05bcbc2f6a8e263d9b72e776",
  "influential_citation_count": 20803
}

Search papers

1 credit per run

Search Semantic Scholar for research papers in relevance order, with available AI one-sentence summaries, citations, and free PDF links. Summaries and direct PDF links may be unavailable for some papers.

What you provide

Field	Type	Required	Description
Field`field`	Text	Optional	Field of study in plain words, for example Medicine or Computer Science.Example: Computer Science
Query`query`	Text	Required	Topic or words from a paper title, for example long covid fatigue.Example: long covid fatigue
End Year`end_year`	Number	Optional	Latest publication year, for example 2025.Example: 2024
Start Year`start_year`	Number	Optional	Earliest publication year, for example 2020.Example: 2021
Max Results`max_results`	Number	Optional	Maximum papers to return, for example 10 (up to 100).Example: 12
Open Access Only`open_access_only`	Yes or no	Optional	Only show open-access papers, for example true.Example: Yes

What you get

Field	Type	Description
Papers`papers`	List
Year`papers[].year`	Number	Example: 2025
Title`papers[].title`	Text	Example: Feasibility and acceptance of transdermal auricular vagus nerve stimulation…
Venue`papers[].venue`	Text	Example: Wiener Klinische Wochenschrift
Authors`papers[].authors`	List
Summary`papers[].summary`	Text	Example: The treatment was found to be safe, with no significant side effects reported…
Paper ID`papers[].paper_id`	Text	Example: 5c9424cb6b209327d75e17424b75613f0863777a
Paper Link`papers[].paper_link`	Text	Example: https://www.semanticscholar.org/paper/5c9424cb6b209327d75e17424b75613f0863777a
Free PDF Link`papers[].free_pdf_link`	Text	Example: https://link.springer.com/content/pdf/10.1007/s00508-025-02501-1.pdf
Number of Citations`papers[].number_of_citations`	Number	Example: 11

Example result

For Query: long covid fatigue

JSON

{
  "papers": [
    {
      "year": 2025,
      "title": "Feasibility and acceptance of transdermal auricular vagus nerve stimulation using a TENS device in females suffering from long COVID fatigue",
      "venue": "Wiener Klinische Wochenschrift",
      "authors": [
        "Veronika Pfoser‐Poschacher",
        "M. Keilani"
      ],
      "summary": "The treatment was found to be safe, with no significant side effects reported; however, further research with larger study groups is needed to confirm these findings and examine the long-term effects …",
      "paper_id": "5c9424cb6b209327d75e17424b75613f0863777a",
      "paper_link": "https://www.semanticscholar.org/paper/5c9424cb6b209327d75e17424b75613f0863777a",
      "free_pdf_link": "https://link.springer.com/content/pdf/10.1007/s00508-025-02501-1.pdf",
      "number_of_citations": 11
    },
    {
      "year": 2024,
      "title": "Efficacy of dual-task augmented reality rehabilitation in non-hospitalized adults with self-reported long COVID fatigue and cognitive impairment: a pilot study",
      "venue": "Neurological Sciences",
      "authors": [
        "M. Deodato",
        "Caterina Qualizza"
      ],
      "summary": "The preliminary results from this study suggest that dual-task rehabilitation could be a feasible protocol to support cognitive symptoms recovery after COVID-19 and could be helpful in those individua…",
      "paper_id": "ae2e60355e15a7131b2e1bdafc2f139b7049ce0e",
      "paper_link": "https://www.semanticscholar.org/paper/ae2e60355e15a7131b2e1bdafc2f139b7049ce0e",
      "free_pdf_link": null,
      "number_of_citations": 17
    }
  ]
}

For developers

Run this workflow from your own code. In Studio, turn on Developer mode and create an API key.

cURL

# First set your key: export FOUS_API_KEY='YOUR_FOUS_API_KEY'
: "${FOUS_API_KEY:?Set FOUS_API_KEY before running this example}"

curl 'https://api.fous.com/v1/query' \
  --fail-with-body --silent --show-error --max-time 120 \
  -H "Authorization: Bearer $FOUS_API_KEY" \
  -H 'Content-Type: application/json' \
  --data-raw '{
  "api": "@semantic-scholar",
  "visibility": "public",
  "operation": "get_author",
  "version": 1,
  "input": {
    "author": "Yoshua Bengio"
  },
  "response": {
    "format": "json"
  }
}'

What you can do with it

Find papers on a research topic within a publication-year range.
Review paper abstracts, authors, venues, and citation counts.
Identify open-access papers with available free PDF links.
Compare researchers using citation totals and h-index.
Compile researchers’ most-cited publications for literature reviews.

Questions

Is Fous affiliated with Semantic Scholar?

No. Fous is not affiliated with Semantic Scholar. This workflow reads the public semanticscholar.org website and returns its data.

How much does it cost?

Each run costs 1 credit. With pay-as-you-go, a credit costs 1¢; monthly plans cost less per credit.

Do I need a Semantic Scholar account?

No. You only need a Fous account.

How current is the data?

Fous gets the data from semanticscholar.org when you run it; repeating the same request within a day may return the saved result. Fous checks this workflow automatically; it last passed a check on Sep 29, 2026.