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Mike D'Arcy

Mike D'Arcy has 2 papers in our library, in 2019–2024, most of them on Question answering, Reasoning; often with Doug Downey, Alexis Ross, Alisa Liu.

2 papers in our library · 2019–2024

OpenAlex · ORCID · Wikidata · h-index 16 · 42 works · 1,001 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 285 times in our library · 5 more in our library without a page yet · ⭐ Paper Stars ranking: #6527

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🔬Allen Institute for Artificial IntelligenceSeattle · United States2024–2026 · 2 paperscurrent🎓University of Southern CaliforniaLos Angeles · United States2001–2024 · 16 papersEmployment since 2001 · Lead Research Engineer, Informatics Systems Research Division🎓Northwestern UniversityEvanston · United States2017–2024 · 10 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksLanguage and Linguistics · 2 worksComputer Science · 1 workArtificial Intelligence · 1 workComputer Vision and Pattern Recognition · 1 workHistory and Philosophy of Science · 1 workLiterature and Literary Theory · 1 work

🧭 Topics 2Research subjects and languages the work is about.Question answering · 1 workReasoning · 1 work

 Works by year

2020s

20241 paper

2010s

20191 paper

 Papers

The most cited first (OpenAlex and our library).

  1. CODAH: An Adversarially-Authored Question Answering Dataset for Common Sense (2019 · 90 citations)
    Pre-trained transformer models such as BERT reached or exceeded human scores on SWAG, a sentence-completion benchmark for commonsense inference.
  2. ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews (2024 · 32 citations)
    Turning reviewer feedback into concrete manuscript revisions requires interpretation and domain reasoning, and there has been little data for studying this in technical writing.

All works

7 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. SciRepEval: A Multi-Format Benchmark for Scientific Document Representations ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetAmanpreet Singh et al.2023 · 128 citations
  2. CODAH: An Adversarially-Authored Question Answering Dataset for Common SenseWorkshop on Evaluating Vector Space Representations for NLPMichael Chen, Mike D'Arcy, Alisa Liu, et al.2019 · 90 citations
  3. MARG: Multi-Agent Review Generation for Scientific Papers ↗arXiv:2401.04259 · no summary yetMike D'Arcy et al.2024 · 76 citations
  4. OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs ↗arXiv:2411.14199 · no summary yetAkari Asai et al.2024 · 62 citations
  5. Synthesizing scientific literature with retrieval-augmented language models ↗Nature · no summary yetAkari Asai et al.2026 · 42 citations
  6. ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer ReviewsAnnual Meeting of the Association for Computational Linguistics (ACL)Mike D'Arcy, Alexis Ross, Erin Bransom, et al.2024 · 32 citations
  7. AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite ↗arXiv:2510.21652 · no summary yetJonathan Bragg et al.2025 · 19 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 285 times (of the 149,439 papers whose bibliographies we read); 53 citing papers with a page here →.

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