---
title: "Who cites Darsh Shah — 314 papers of our library"
description: "314 papers of the Elamur Research library cite the works of Darsh Shah, found in their bibliographies; the most cited first."
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---
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# Who cites Darsh Shah

325 citations of their works from 314 papers of our library (of the 149,439 whose bibliographies we read) · 48 with a page here, the most cited first · [← Darsh Shah](https://md.research.elamur.ai/free/en/authors/darsh-shah/)

1. **[MTEB: Massive Text Embedding Benchmark](https://md.research.elamur.ai/free/en/papers/muennighoff-2022-mteb-massive-text-embedding-benchmark/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Niklas Muennighoff, Nouamane Tazi, Loïc Magne, et al.*2022 · 1,032 citations*
2. **[ERASER: A Benchmark to Evaluate Rationalized NLP Models](https://md.research.elamur.ai/free/en/papers/deyoung-2020-eraser-benchmark-evaluate-rationalized-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jay DeYoung, Sarthak Jain, Nazneen Fatema Rajani, et al.*2020 · 832 citations*
3. **[Fact or Fiction: Verifying Scientific Claims](https://md.research.elamur.ai/free/en/papers/wadden-2020-fact-or-fiction-verifying-scientific/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Wadden, Shanchuan Lin, Kyle Lo, et al.*2020 · 709 citations*
4. **[A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 647 citations*
5. **[BioMistral: A Collection of Open-Source Pretrained Large Language Models for Medical Domains](https://md.research.elamur.ai/free/en/papers/labrak-2024-biomistral-collection-open-source-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanis Labrak, Adrien Bazoge, Emmanuel Morin, et al.*2024 · 409 citations*
6. **[Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/rastogi-2019-towards-scalable-multi-domain-conversational/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Abhinav Rastogi, Xiaoxue Zang, Srinivas Sunkara, et al.*2019 · 374 citations*
7. **[Neural Unsupervised Domain Adaptation in NLP–-A Survey](https://md.research.elamur.ai/free/en/papers/ramponi-2020-neural-unsupervised-domain-adaptation-nlp/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Alan Ramponi, Barbara Plank*2020 · 336 citations*
8. **[Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/savoldi-2021-gender-bias-machine-translation/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, et al.*2021 · 310 citations*
9. **[Hate Speech Detection and Racial Bias Mitigation in Social Media based on BERT model](https://md.research.elamur.ai/free/en/papers/mozafari-2020-hate-speech-detection-racial-bias/) [PLoS ONE](https://md.research.elamur.ai/free/en/venues/plos-one/)**Marzieh Mozafari, Reza Farahbakhsh, Noel Crespi*2020 · 305 citations*
10. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
11. **[Get Your Vitamin C! Robust Fact Verification with Contrastive Evidence](https://md.research.elamur.ai/free/en/papers/schuster-2021-get-your-vitamin-c-robust/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tal Schuster, Adam Fisch, Regina Barzilay*2021 · 290 citations*
12. **[A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directions](https://md.research.elamur.ai/free/en/papers/wu-2025-survey-llm-generated-text-detection/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Junchao Wu, Shu Yang, Runzhe Zhan, et al.*2025 · 277 citations*
13. **[Augmented SBERT: Data Augmentation Method for Improving Bi-Encoders for Pairwise Sentence Scoring Tasks](https://md.research.elamur.ai/free/en/papers/thakur-2021-augmented-sbert-data-augmentation-method/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nandan Thakur, Nils Reimers, Johannes Daxenberger, et al.*2021 · 276 citations*
14. **[Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network](https://md.research.elamur.ai/free/en/papers/hou-2020-few-shot-slot-tagging-collapsed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutai Hou, Wanxiang Che, Yongkui Lai, et al.*2020 · 265 citations*
15. **[A Holistic Approach to Undesired Content Detection in the Real World](https://md.research.elamur.ai/free/en/papers/markov-2022-holistic-approach-undesired-content-detection/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Todor Markov, Chong Zhang, Sandhini Agarwal, et al.*2022 · 263 citations*
16. [**Red teaming ChatGPT via Jailbreaking: Bias, Robustness, Reliability and Toxicity arXiv:2301.12867**Terry Yue Zhuo, Yujin Huang, Chunyang Chen, et al.*2023 · 249 citations*](https://md.research.elamur.ai/free/en/papers/zhuo-2023-red-teaming-chatgpt-jailbreaking-bias/)
17. **[Automatic Detection of Machine Generated Text: A Critical Survey](https://md.research.elamur.ai/free/en/papers/jawahar-2020-automatic-detection-machine-generated-text/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Ganesh Jawahar, Muhammad Abdul-Mageed, Laks Lakshmanan V.S.*2020 · 247 citations*
18. **[HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification](https://md.research.elamur.ai/free/en/papers/jiang-2020-hover-dataset-many-hop-fact/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichen Jiang, Shikha Bordia, Zheng Zhong, et al.*2020 · 228 citations*
19. **[A Survey on Stance Detection for Mis- and Disinformation Identification](https://md.research.elamur.ai/free/en/papers/hardalov-2022-survey-stance-detection-mis-disinformation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2022 · 188 citations*
20. **[Multi-Source Cross-Lingual Model Transfer: Learning What to Share](https://md.research.elamur.ai/free/en/papers/chen-2019-multi-source-cross-lingual-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xilun Chen, Ahmed Hassan Awadallah, Hany Hassan, et al.*2019 · 162 citations*
21. **[Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance](https://md.research.elamur.ai/free/en/papers/utama-2020-mind-trade-off-debiasing-nlu/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prasetya Ajie Utama, Nafise Sadat Moosavi, Iryna Gurevych*2020 · 159 citations*
22. **[The Limitations of Stylometry for Detecting Machine-Generated Fake News](https://md.research.elamur.ai/free/en/papers/schuster-2020-limitations-stylometry-detecting-machine-generated/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Tal Schuster, Roei Schuster, Darsh J. Shah, et al.*2020 · 151 citations*
23. **[TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2021-turingbench-benchmark-environment-turing-test/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adaku Uchendu, Zeyu Ma, Thai Le, et al.*2021 · 140 citations*
24. **[End-to-End Bias Mitigation by Modelling Biases in Corpora](https://md.research.elamur.ai/free/en/papers/mahabadi-2020-end-end-bias-mitigation-modelling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson*2020 · 111 citations*
25. **[RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors](https://md.research.elamur.ai/free/en/papers/dugan-2024-raid-shared-benchmark-robust-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liam Dugan, Alyssa Hwang, Filip Trhlík, et al.*2024 · 110 citations*
26. [**MMTEB: Massive Multilingual Text Embedding Benchmark arXiv:2502.13595**Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.*2025 · 103 citations*](https://md.research.elamur.ai/free/en/papers/enevoldsen-2025-mmteb-massive-multilingual-text-embedding/)
27. **[Generating Data to Mitigate Spurious Correlations in Natural Language Inference Datasets](https://md.research.elamur.ai/free/en/papers/wu-2022-generating-data-mitigate-spurious-correlations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxiang Wu, Matt Gardner, Pontus Stenetorp, et al.*2022 · 99 citations*
28. **[DialFact: A Benchmark for Fact-Checking in Dialogue](https://md.research.elamur.ai/free/en/papers/gupta-2022-dialfact-benchmark-fact-checking-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 97 citations*
29. **[Cross-Domain Label-Adaptive Stance Detection](https://md.research.elamur.ai/free/en/papers/hardalov-2021-cross-domain-label-adaptive-stance/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Momchil Hardalov, Arnav Arora, Preslav Nakov, et al.*2021 · 96 citations*
30. **[Fact Checking with Insufficient Evidence](https://md.research.elamur.ai/free/en/papers/atanasova-2022-fact-checking-insufficient-evidence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2022 · 46 citations*
31. **[AmbiFC: Fact-Checking Ambiguous Claims with Evidence](https://md.research.elamur.ai/free/en/papers/glockner-2024-ambifc-fact-checking-ambiguous-claims/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Max Glockner, Ieva Staliūnaitė, James Thorne, et al.*2024 · 42 citations*
32. [**Interpretable Unified Language Checking arXiv:2304.03728**Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang, et al.*2023 · 32 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-interpretable-unified-language-checking/)
33. [**Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models arXiv:2005.14709**Viktor Schlegel, Goran Nenadic, Riza Batista-Navarro*2020 · 24 citations*](https://md.research.elamur.ai/free/en/papers/schlegel-2020-leaderboards-survey-methods-revealing-weaknesses/)
34. [**Shallow Synthesis of Knowledge in GPT-Generated Texts: A Case Study in Automatic Related Work Composition arXiv:2402.12255**Anna Martin-Boyle; Aahan Tyagi; Marti A. Hearst;, Dongyeop Kang*2024 · 16 citations*](https://md.research.elamur.ai/free/en/papers/martin-boyle-2024-shallow-synthesis-knowledge-gpt-generated/)
35. [**Rethinking Reflection in Pre-Training arXiv:2504.04022**Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.*2025 · 15 citations*](https://md.research.elamur.ai/free/en/papers/shah-2025-rethinking-reflection-pre-training/)
36. **[Prompting for explanations improves Adversarial NLI. Is this true? \Yes\ it is \true\ because ıt weakens superficial cues\](https://md.research.elamur.ai/free/en/papers/kavumba-2023-prompting-explanations-improves-adversarial-nli/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Pride Kavumba, Ana Brassard, Benjamin Heinzerling, et al.*2023 · 14 citations*
37. **[A Reality Check on Context Utilisation for Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/hagstrom-2025-reality-check-context-utilisation-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lovisa Hagström, Sara Vera Marjanovic, Haeun Yu, et al.*2025 · 13 citations*
38. **[Looking at the Overlooked: An Analysis on the Word-Overlap Bias in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/rajaee-2022-looking-overlooked-analysis-word-overlap/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sara Rajaee, Yadollah Yaghoobzadeh, Mohammad Taher Pilehvar*2022 · 13 citations*
39. **[Towards the Necessity for Debiasing Natural Language Inference Datasets](https://md.research.elamur.ai/free/en/papers/panenghat-2020-necessity-debiasing-natural-language-inference/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Mithun Paul Panenghat, Sandeep Suntwal, Faiz Rafique, et al.*2020 · 13 citations*
40. **[A Generative Approach for Mitigating Structural Biases in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/asael-2022-generative-approach-mitigating-structural-biases/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Dimion Asael, Zachary Ziegler, Yonatan Belinkov*2022 · 10 citations*
41. **[SSR: Utilizing Simplified Stance Reasoning Process for Robust Stance Detection](https://md.research.elamur.ai/free/en/papers/yuan-2022-ssr-utilizing-simplified-stance-reasoning/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jianhua Yuan, Yanyan Zhao, Yanyue Lu, et al.*2022 · 6 citations*
42. **[A Survey on Combating Hate Speech through Detection and Prevention in English](https://md.research.elamur.ai/free/en/papers/kapil-2024-survey-combating-hate-speech-through/) [International Conference on Natural Language Processing (ICON)](https://md.research.elamur.ai/free/en/venues/icon/)**Prashant Kapil, Asif Ekbal*2024 · 3 citations*
43. **[HTMuon: Improving Muon via Heavy-Tailed Spectral Correction](https://md.research.elamur.ai/free/en/papers/pang-2026-htmuon-improving-muon-heavy-tailed/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Pang, Yujie Fang, Zihang Liu, et al.*2026 · 2 citations*
44. **[Corpus and Baselines for Distinguishing Authentic, AI-Generated, and AI-Enhanced Resumes](https://md.research.elamur.ai/free/en/papers/loizidou-2026-corpus-baselines-distinguishing-authentic-ai/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Andrea Loizidou, Anshu Kiran Sharma, Adrian Esquivel, et al.*2026*
45. **[Evidence Grounding vs. Memorization: Why Neural Semantics Matter for Knowledge Graph Fact Verification](https://md.research.elamur.ai/free/en/papers/upadhyay-2026-evidence-grounding-vs-memorization-why/) [Fact Extraction and VERification Workshop (FEVER)](https://md.research.elamur.ai/free/en/venues/fever/)**Ankit Kumar Upadhyay, John S. Erickson, Deborah L. McGuinness*2026*
46. **[Mask-to-Correct+: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction](https://md.research.elamur.ai/free/en/papers/santra-2026-mask-correct-leveraging-retriever-diversity/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Payel Santra, Lavisha Sharma, Madhusudan Ghosh, et al.*2026*
47. **[Measuring and Mitigating Shortcut Reliance in Language Models with Probe-Based Representation Entanglement](https://md.research.elamur.ai/free/en/papers/singh-2026-measuring-mitigating-shortcut-reliance-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Divyajot Singh*2026*
48. **[Pushing the Frontiers of Scientific Fact-Checking: The SCINLP Dataset](https://md.research.elamur.ai/free/en/papers/maab-2026-pushing-frontiers-scientific-fact-checking/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Iffat Maab, Junichi Yamagishi*2026*

266 more citing papers of our library have no page here yet.

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