🧑‍🔬 Darsh Shah

🏛️ Affiliations

🎓Massachusetts Institute of TechnologyCambridge · United States2018–2021 · 14 paperscurrent🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge · United States2018–2021 · 8 paperscurrent

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.

📅 Works by year

2020s

2010s

📄 Papers

The most cited first (OpenAlex and our library).

1. Towards Debiasing Fact Verification Models (2019 · 301 citations)
   The paper examines whether the FEVER fact-checking benchmark actually forces models to reason over evidence.
2. The Limitations of Stylometry for Detecting Machine-Generated Fake News (2020 · 151 citations)
   The paper investigates whether stylometry, meaning detection based on stylistic cues, is able to tell apart harmful and acceptable applications of language models (LMs).

All works

10 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. Towards Debiasing Fact Verification ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tal Schuster, Darsh Shah, Yun Jie Serene Yeo, et al.2019 · 301 citations
2. Multi-Source Domain Adaptation with Mixture of Experts ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetJiang Guo, Darsh Shah, Regina Barzilay2018 · 210 citations
3. The Limitations of Stylometry for Detecting Machine-Generated Fake NewsComputational LinguisticsTal Schuster, Roei Schuster, Darsh J. Shah, et al.2020 · 151 citations
4. Robust Zero-Shot Cross-Domain Slot Filling with Example Values ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetDarsh Shah et al.2019 · 128 citations
5. Adversarial Domain Adaptation for Duplicate Question Detection ↗Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing · no summary yetDarsh Shah et al.2018 · 109 citations
6. Nutri-bullets Hybrid: Consensual Multi-document Summarization ↗Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetDarsh Shah et al.2021 · 12 citations
7. Practical Efficiency of Muon for Pretraining ↗arXiv (Cornell University) · no summary yetEssential AI et al.2025 · 10 citations
8. Nutribullets Hybrid: Multi-document Health Summarization ↗arXiv (Cornell University) · no summary yetDarsh Shah et al.2021 · 9 citations
9. Generating Related Work ↗arXiv (Cornell University) · no summary yetDarsh Shah, Regina Barzilay2021 · 3 citations
10. Reducing Target Group Bias in Hate Speech Detectors ↗arXiv (Cornell University) · no summary yetDarsh Shah et al.2021 · 1 citation

🤝 Co-authors here

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

• Regina Barzilay ×2
• Tal Schuster ×2
• Enrico Santus
• Roei Schuster

Venues

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

• Conference on Empirical Methods in Natural Language Processing (EMNLP) ×3: EMNLP 2019
• Computational Linguistics: Computational Linguistics 2020
• Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
• Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

🔗 Cited by

Papers of our library cite their works 325 times (of the 149,439 papers whose bibliographies we read); 48 citing papers with a page here →.

Updated 30 October 2026

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