---
title: "Who cites Tristan Thrush — 272 papers of our library"
description: "272 papers of the Elamur Research library cite the works of Tristan Thrush, found in their bibliographies; the most cited first."
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---
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# Who cites Tristan Thrush

276 citations of their works from 272 papers of our library (of the 141,840 whose bibliographies we read) · 30 with a page here, the most cited first · [← Tristan Thrush](https://md.research.elamur.ai/free/en/authors/tristan-thrush/)

1. [**Multitask Prompted Training Enables Zero-Shot Task Generalization arXiv:2110.08207**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,581 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/)
2. **[ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/hartvigsen-2022-toxigen-large-scale-machine-generated/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, et al.*2022 · 571 citations*
3. **[BBQ: A hand-built bias benchmark for question answering](https://md.research.elamur.ai/free/en/papers/parrish-2022-bbq-hand-built-bias-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alicia Parrish, Angelica Chen, Nikita Nangia, et al.*2022 · 488 citations*
4. [**The Falcon Series of Open Language Models arXiv:2311.16867**Ebtesam Almazrouei, Hamza Alobeidli, Abdulaziz Alshamsi, et al.*2023 · 436 citations*](https://md.research.elamur.ai/free/en/papers/almazrouei-2023-falcon-series-open-language-models/)
5. **[Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection](https://md.research.elamur.ai/free/en/papers/sap-2022-annotators-attitudes-how-annotator-beliefs/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Maarten Sap, Swabha Swayamdipta, Laura Vianna, et al.*2022 · 365 citations*
6. [**Large Language Models Struggle to Learn Long-Tail Knowledge arXiv:2211.08411**Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.*2022 · 353 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-large-language-models-struggle-learn/)
7. **[ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers](https://md.research.elamur.ai/free/en/papers/yao-2022-zeroquant-efficient-affordable-post-training/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, et al.*2022 · 302 citations*
8. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 300 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
9. **[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 · 254 citations*
10. [**XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models arXiv:2308.01263**Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.*2023 · 227 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2023-xstest-test-suite-identifying-exaggerated/)
11. **[Two Contrasting Data Annotation Paradigms for Subjective NLP Tasks](https://md.research.elamur.ai/free/en/papers/rottger-2022-two-contrasting-data-annotation-paradigms/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Paul Röttger, Bertie Vidgen, Dirk Hovy, et al.*2022 · 219 citations*
12. **[HateCheck: Functional Tests for Hate Speech Detection Models](https://md.research.elamur.ai/free/en/papers/rottger-2021-hatecheck-functional-tests-hate-speech/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Röttger, Bertie Vidgen, Dong Nguyen, et al.*2021 · 203 citations*
13. **[What matters when building vision-language models?](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2024-matters-building-vision-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.*2024 · 195 citations*
14. **[SemEval-2023 Task 10: Explainable Detection of Online Sexism](https://md.research.elamur.ai/free/en/papers/kirk-2023-semeval-2023-task-10-explainable/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Hannah Kirk, Wenjie Yin, Bertie Vidgen, et al.*2023 · 185 citations*
15. **[OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents](https://md.research.elamur.ai/free/en/papers/lauren-ccon-2023-obelics-open-web-scale-filtered/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugo Laurençon, Lucile Saulnier, Leo Tronchon, et al.*2023 · 183 citations*
16. **[CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages](https://md.research.elamur.ai/free/en/papers/nguyen-2023-culturax-cleaned-enormous-multilingual-dataset/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, et al.*2023 · 180 citations*
17. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 178 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
18. **[Do All Languages Cost the Same? Tokenization in the Era of Commercial Language Models](https://md.research.elamur.ai/free/en/papers/ahia-2023-do-all-languages-cost-same/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orevaoghene Ahia, Sachin Kumar, Hila Gonen, et al.*2023 · 164 citations*
19. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*
20. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 123 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
21. **[Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speech](https://md.research.elamur.ai/free/en/papers/fanton-2021-human-loop-data-collection-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, et al.*2021 · 118 citations*
22. **[Investigating Reasons for Disagreement in Natural Language Inference](https://md.research.elamur.ai/free/en/papers/jiang-2022-investigating-reasons-disagreement-natural-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nan-Jiang Jiang, Marie-Catherine de Marneffe*2022 · 104 citations*
23. **[BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting](https://md.research.elamur.ai/free/en/papers/yong-2023-bloom-1-adding-language-support/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Xin Yong, Hailey Schoelkopf, Niklas Muennighoff, et al.*2023 · 101 citations*
24. **[NLPositionality: Characterizing Design Biases of Datasets and Models](https://md.research.elamur.ai/free/en/papers/santy-2023-nlpositionality-characterizing-design-biases-datasets/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.*2023 · 88 citations*
25. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
26. [**Investigating the Translation Performance of a Large Multilingual Language Model: the Case of BLOOM arXiv:2303.01911**Rachel Bawden, François Yvon*2023 · 85 citations*](https://md.research.elamur.ai/free/en/papers/bawden-2023-investigating-translation-performance-large-multilingual/)
27. [**He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics**Nanjiang Jiang, Marie-Catherine de Marneffe*2021 · 21 citations*](https://md.research.elamur.ai/free/en/papers/jiang-2021-he-thinks-he-knows-better/)
28. **[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*
29. **[IEKG: A Commonsense Knowledge Graph for Idiomatic Expressions](https://md.research.elamur.ai/free/en/papers/zeng-2023-iekg-commonsense-knowledge-graph-idiomatic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziheng Zeng, Kellen Tan Cheng, Srihari Venkat Nanniyur, et al.*2023 · 11 citations*
30. **[Explainable AI for Ethical Counter Speech Generation in Hate Speech Mitigation](https://md.research.elamur.ai/free/en/papers/ridoy-2026-explainable-ai-ethical-counter-speech/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Ashiful Islam Ridoy, Mohammed Faisal, Yogesh Kumar, et al.*2026*

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

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