---
title: "Who cites RoBERTa: A — page 4 — 9,837 citing papers"
description: "9,837 papers of the Elamur Research library cite «RoBERTa: A Robustly Optimized BERT Pretraining Approach», found in their…"
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---
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# Who cites «RoBERTa: A Robustly Optimized BERT Pretraining Approach»

9,837 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1406 with a page here, the most cited first · page 4 of 15 · 301–400 · [← back to «RoBERTa: A Robustly Optimized BERT Pretraining Approach»](https://md.research.elamur.ai/free/en/papers/liu-2019-roberta-robustly-optimized-bert-pretraining/)

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301. **[LexGLUE: A Benchmark Dataset for Legal Language Understanding in English](https://md.research.elamur.ai/free/en/papers/chalkidis-2022-lexglue-benchmark-dataset-legal-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ilias Chalkidis, Abhik Jana, Dirk Hartung, et al.*2022 · 239 citations*
302. **[FUDGE: Controlled Text Generation With Future Discriminators](https://md.research.elamur.ai/free/en/papers/yang-2021-fudge-controlled-text-generation-future/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kevin Yang, Dan Klein*2021 · 239 citations*
303. **[CoLAKE: Contextualized Language and Knowledge Embedding](https://md.research.elamur.ai/free/en/papers/sun-2020-colake-contextualized-language-knowledge-embedding/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianxiang Sun, Yunfan Shao, Xipeng Qiu, et al.*2020 · 239 citations*
304. **[mGTE: Generalized Long-Context Text Representation and Reranking Models for Multilingual Text Retrieval](https://md.research.elamur.ai/free/en/papers/zhang-2024-mgte-generalized-long-context-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xin Zhang, Yanzhao Zhang, Dingkun Long, et al.*2024 · 237 citations*
305. **[Evaluating Commonsense in Pre-trained Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2019-evaluating-commonsense-pre-trained-language/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Xuhui Zhou, Yue Zhang, Leyang Cui, et al.*2019 · 235 citations*
306. **[SemEval-2022 Task 5: Multimedia Automatic Misogyny Identification](https://md.research.elamur.ai/free/en/papers/fersini-2022-semeval-2022-task-5-multimedia/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Elisabetta Fersini, Francesca Gasparini, Giulia Rizzi, et al.*2022 · 234 citations*
307. **[Self-Guided Contrastive Learning for BERT Sentence Representations](https://md.research.elamur.ai/free/en/papers/kim-2021-self-guided-contrastive-learning-bert/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taeuk Kim, Kang Min Yoo, Sang-goo Lee*2021 · 234 citations*
308. **[Automatically Identifying Words That Can Serve as Labels for Few-Shot Text Classification](https://md.research.elamur.ai/free/en/papers/schick-2020-automatically-identifying-words-that-can/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Timo Schick, Helmut Schmid, Hinrich Schütze*2020 · 234 citations*
309. [**How Context Affects Language Models' Factual Predictions arXiv:2005.04611**Fabio Petroni, Patrick Lewis, Aleksandra Piktus, et al.*2020 · 234 citations*](https://md.research.elamur.ai/free/en/papers/petroni-2020-context-affects-language-models-factual/)
310. **[TweepFake: about Detecting Deepfake Tweets](https://md.research.elamur.ai/free/en/papers/fagni-2020-tweepfake-about-detecting-deepfake-tweets/) [PLoS ONE](https://md.research.elamur.ai/free/en/venues/plos-one/)**Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, et al.*2020 · 234 citations*
311. **[Hurdles to Progress in Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/krishna-2021-hurdles-progress-long-form-question/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kalpesh Krishna, Aurko Roy, Mohit Iyyer*2021 · 233 citations*
312. **[Detecting Hallucinated Content in Conditional Neural Sequence Generation](https://md.research.elamur.ai/free/en/papers/zhou-2021-detecting-hallucinated-content-conditional-neural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chunting Zhou, Graham Neubig, Jiatao Gu, et al.*2021 · 232 citations*
313. **[Moving Down the Long Tail of Word Sense Disambiguation with Gloss Informed Bi-encoders](https://md.research.elamur.ai/free/en/papers/blevins-2020-moving-down-long-tail-word/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Terra Blevins, Luke Zettlemoyer*2020 · 232 citations*
314. **[Coreferential Reasoning Learning for Language Representation](https://md.research.elamur.ai/free/en/papers/ye-2020-coreferential-reasoning-learning-language-representation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Deming Ye, Yankai Lin, Jiaju Du, et al.*2020 · 228 citations*
315. **[Learning to Faithfully Rationalize by Construction](https://md.research.elamur.ai/free/en/papers/jain-2020-learning-faithfully-rationalize-construction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sarthak Jain, Sarah Wiegreffe, Yuval Pinter, et al.*2020 · 225 citations*
316. **[A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages](https://md.research.elamur.ai/free/en/papers/suarez-2020-monolingual-approach-contextualized-word-embeddings/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pedro Javier Ortiz Suárez, Laurent Romary, Benoît Sagot*2020 · 222 citations*
317. **[Reasoning Over Semantic-Level Graph for Fact Checking](https://md.research.elamur.ai/free/en/papers/zhong-2020-reasoning-over-semantic-level-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wanjun Zhong, Jingjing Xu, Duyu Tang, et al.*2020 · 222 citations*
318. **[Unsupervised Question Decomposition for Question Answering](https://md.research.elamur.ai/free/en/papers/perez-2020-unsupervised-question-decomposition-question-answering/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Patrick Lewis, Wen-tau Yih, et al.*2020 · 222 citations*
319. **[Structured Pruning Learns Compact and Accurate Models](https://md.research.elamur.ai/free/en/papers/xia-2022-structured-pruning-learns-compact-accurate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengzhou Xia, Zexuan Zhong, Danqi Chen*2022 · 221 citations*
320. [**AlpaGasus: Training A Better Alpaca with Fewer Data arXiv:2307.08701**Lichang Chen, Shiyang Li, Jun Yan, et al.*2023 · 220 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-alpagasus-training-better-alpaca-fewer/)
321. **[Multilingual Translation from Denoising Pre-Training](https://md.research.elamur.ai/free/en/papers/tang-2021-multilingual-translation-denoising-pre-training/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuqing Tang, Chau Tran, Xian Li, et al.*2021 · 220 citations*
322. [**FOLIO: Natural Language Reasoning with First-Order Logic arXiv:2209.00840**Simeng Han, Hailey Schoelkopf, Yilun Zhao, et al.*2022 · 219 citations*](https://md.research.elamur.ai/free/en/papers/han-2022-folio-natural-language-reasoning-first/)
323. **[Maieutic Prompting: Logically Consistent Reasoning with Recursive Explanations](https://md.research.elamur.ai/free/en/papers/jung-2022-maieutic-prompting-logically-consistent-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jaehun Jung, Lianhui Qin, Sean Welleck, et al.*2022 · 219 citations*
324. **[SpeechT5: Unified-Modal Encoder-Decoder Pre-Training for Spoken Language Processing](https://md.research.elamur.ai/free/en/papers/ao-2022-speecht5-unified-modal-encoder-decoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Junyi Ao, Rui Wang, Long Zhou, et al.*2022 · 219 citations*
325. [**Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models arXiv:2308.16149**Neha Sengupta, Sunil Kumar Sahu, Bokang Jia, et al.*2023 · 218 citations*](https://md.research.elamur.ai/free/en/papers/sengupta-2023-jais-jais-chat-arabic-centric/)
326. **[Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-Trained Language Models](https://md.research.elamur.ai/free/en/papers/lin-2020-birds-have-four-legs-numersense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bill Yuchen Lin, Seyeon Lee, Rahul Khanna, et al.*2020 · 218 citations*
327. [**Evaluating the Logical Reasoning Ability of ChatGPT and GPT-4 arXiv:2304.03439**Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-logical-reasoning-ability-chatgpt/)
328. [**Language Models are Super Mario: Absorbing Abilities from Homologous Models as a Free Lunch arXiv:2311.03099**Le Yu, Bowen Yu, Haiyang Yu, et al.*2023 · 217 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-language-models-super-mario-absorbing/)
329. **[Making Language Models Better Reasoners with Step-Aware Verifier](https://md.research.elamur.ai/free/en/papers/li-2023-making-language-models-better-reasoners/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifei Li, Zeqi Lin, Shizhuo Zhang, et al.*2023 · 217 citations*
330. **[Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models](https://md.research.elamur.ai/free/en/papers/iv-2022-cutting-down-prompts-parameters-simple/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Robert Logan IV, Ivana Balazevic, Eric Wallace, et al.*2022 · 216 citations*
331. [**LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders arXiv:2404.05961**Parishad BehnamGhader, Vaibhav Adlakha, Marius Mosbach, et al.*2024 · 213 citations*](https://md.research.elamur.ai/free/en/papers/behnamghader-2024-llm2vec-large-language-models-secretly/)
332. [**Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP arXiv:2103.00453**Timo Schick, Sahana Udupa, Hinrich Schutze*2021 · 213 citations*](https://md.research.elamur.ai/free/en/papers/schick-2021-self-diagnosis-self-debiasing-proposal/)
333. **[An Unsupervised Sentence Embedding Method by Mutual Information Maximization](https://md.research.elamur.ai/free/en/papers/zhang-2020-unsupervised-sentence-embedding-method-mutual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yan Zhang, Ruidan He, Zuozhu Liu, et al.*2020 · 213 citations*
334. **[Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!](https://md.research.elamur.ai/free/en/papers/ma-2023-large-language-model-is-not/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yubo Ma, Yixin Cao, Yong Hong, et al.*2023 · 212 citations*
335. **[Sources of Hallucination by Large Language Models on Inference Tasks](https://md.research.elamur.ai/free/en/papers/mckenna-2023-sources-hallucination-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nick McKenna, Tianyi Li, Liang Cheng, et al.*2023 · 212 citations*
336. **[Explaining Answers with Entailment Trees](https://md.research.elamur.ai/free/en/papers/dalvi-2021-explaining-answers-entailment-trees/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bhavana Dalvi, Peter Jansen, Oyvind Tafjord, et al.*2021 · 211 citations*
337. [**Generating Training Data with Language Models: Towards Zero-Shot Language Understanding arXiv:2202.04538**Yu Meng, Jiaxin Huang, Yu Zhang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/meng-2022-generating-training-data-language-models/)
338. [**Prompting GPT-3 To Be Reliable arXiv:2210.09150**Chenglei Si, Zhe Gan, Zhengyuan Yang, et al.*2022 · 210 citations*](https://md.research.elamur.ai/free/en/papers/si-2022-prompting-gpt-3-reliable/)
339. **[Active Example Selection for In-Context Learning](https://md.research.elamur.ai/free/en/papers/zhang-2022-active-example-selection-context-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yiming Zhang, Shi Feng, Chenhao Tan*2022 · 209 citations*
340. **[Merging Models with Fisher-Weighted Averaging](https://md.research.elamur.ai/free/en/papers/matena-2021-merging-models-fisher-weighted-averaging/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Michael Matena, Colin Raffel*2021 · 208 citations*
341. **[Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space](https://md.research.elamur.ai/free/en/papers/li-2020-optimus-organizing-sentences-pre-trained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chunyuan Li, Xiang Gao, Yuan Li, et al.*2020 · 208 citations*
342. **[Training Question Answering Models From Synthetic Data](https://md.research.elamur.ai/free/en/papers/puri-2020-training-question-answering-models-synthetic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Raul Puri, Ryan Spring, Mohammad Shoeybi, et al.*2020 · 208 citations*
343. **[Language Model Tokenizers Introduce Unfairness Between Languages](https://md.research.elamur.ai/free/en/papers/petrov-2023-language-model-tokenizers-introduce-unfairness/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Aleksandar Petrov, Emanuele La Malfa, Philip H. S. Torr, et al.*2023 · 206 citations*
344. **[Automated Concatenation of Embeddings for Structured Prediction](https://md.research.elamur.ai/free/en/papers/wang-2021-automated-concatenation-embeddings-structured-prediction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Wang, Yong Jiang, Nguyen Bach, et al.*2021 · 206 citations*
345. **[Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning](https://md.research.elamur.ai/free/en/papers/wang-2021-improving-named-entity-recognition-external/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinyu Wang, Yong Jiang, Nguyen Bach, et al.*2021 · 206 citations*
346. **[CharacterBERT: Reconciling ELMo and BERT for Word-Level Open-Vocabulary Representations From Characters](https://md.research.elamur.ai/free/en/papers/boukkouri-2020-characterbert-reconciling-elmo-bert-word/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Hicham El Boukkouri, Olivier Ferret, Thomas Lavergne, et al.*2020 · 206 citations*
347. **[On the Effectiveness of Adapter-based Tuning for Pretrained Language Model Adaptation](https://md.research.elamur.ai/free/en/papers/he-2021-effectiveness-adapter-based-tuning-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruidan He, Linlin Liu, Hai Ye, et al.*2021 · 204 citations*
348. **[DyLoRA: Parameter-Efficient Tuning of Pre-trained Models using Dynamic Search-Free Low-Rank Adaptation](https://md.research.elamur.ai/free/en/papers/valipour-2023-dylora-parameter-efficient-tuning-pre/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Mojtaba Valipour, Mehdi Rezagholizadeh, Ivan Kobyzev, et al.*2023 · 203 citations*
349. **[Structured Pruning of Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2020-structured-pruning-large-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ziheng Wang, Jeremy Wohlwend, Tao Lei*2020 · 202 citations*
350. **[A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 200 citations*
351. **[Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning](https://md.research.elamur.ai/free/en/papers/xu-2021-raise-child-large-language-model/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Runxin Xu, Fuli Luo, Zhiyuan Zhang, et al.*2021 · 200 citations*
352. **[A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation](https://md.research.elamur.ai/free/en/papers/huang-2023-survey-safety-trustworthiness-large-language/) [Artificial Intelligence Review](https://md.research.elamur.ai/free/en/venues/artificial-intelligence-review/)**Xiaowei Huang, Wenjie Ruan, Wei Huang, et al.*2023 · 199 citations*
353. **[Position Information in Transformers: An Overview](https://md.research.elamur.ai/free/en/papers/dufter-2022-position-information-transformers-overview/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Philipp Dufter, Martin Schmitt, Hinrich Schütze*2022 · 198 citations*
354. [**COCO-LM: Correcting and Contrasting Text Sequences for Language Model Pretraining arXiv:2102.08473**Yu Meng, Chenyan Xiong, Payal Bajaj, et al.*2021 · 198 citations*](https://md.research.elamur.ai/free/en/papers/meng-2021-coco-lm-correcting-contrasting-text/)
355. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 198 citations*
356. **[Towards Faithful Model Explanation in NLP: A Survey](https://md.research.elamur.ai/free/en/papers/lyu-2024-faithful-model-explanation-nlp-survey/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Qing Lyu, Marianna Apidianaki, Chris Callison-Burch*2024 · 197 citations*
357. **[The Unreliability of Explanations in Few-shot Prompting for Textual Reasoning](https://md.research.elamur.ai/free/en/papers/ye-2022-unreliability-explanations-few-shot-prompting/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xi Ye, Greg Durrett*2022 · 196 citations*
358. **[Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering](https://md.research.elamur.ai/free/en/papers/honovich-2021-q-2-evaluating-factual-consistency/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Or Honovich, Leshem Choshen, Roee Aharoni, et al.*2021 · 196 citations*
359. **[Authorship Attribution for Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2020-authorship-attribution-neural-text-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Adaku Uchendu, Thai Le, Kai Shu, et al.*2020 · 196 citations*
360. **[What Can We Learn from Collective Human Opinions on Natural Language Inference Data?](https://md.research.elamur.ai/free/en/papers/nie-2020-what-can-we-learn-collective/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yixin Nie, Xiang Zhou, Mohit Bansal*2020 · 196 citations*
361. **[Retrieval Augmented Code Generation and Summarization](https://md.research.elamur.ai/free/en/papers/parvez-2021-retrieval-augmented-code-generation-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Md Rizwan Parvez, Wasi Ahmad, Saikat Chakraborty, et al.*2021 · 193 citations*
362. **[That is a Known Lie: Detecting Previously Fact-Checked Claims](https://md.research.elamur.ai/free/en/papers/shaar-2020-that-is-known-lie-detecting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shaden Shaar, Nikolay Babulkov, Giovanni Da San Martino, et al.*2020 · 193 citations*
363. **[Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts](https://md.research.elamur.ai/free/en/papers/guo-2022-auto-debias-debiasing-masked-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yue Guo, Yi Yang, Ahmed Abbasi*2022 · 191 citations*
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