🧑‍🔬 Who cites Rebecca Qian

102 citations of their works from 102 papers of our library (of the 149,439 whose bibliographies we read) · 24 with a page here, the most cited first · ← Rebecca Qian

1. DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningNatureDeepSeek-AI, Daya Guo, Dejian Yang, et al.2025 · 4,728 citations
2. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
3. XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language ModelsarXiv:2308.01263Paul Rottger, Hannah Rose Kirk, Bertie Vidgen, et al.2023 · 244 citations
4. SeamlessM4T: Massively Multilingual & Multimodal Machine TranslationarXiv:2308.11596Seamless Communication, Loic Barrault, Yu-An Chung, et al.2023 · 183 citations
5. “I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor DatasetConference on Empirical Methods in Natural Language Processing (EMNLP)Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.2022 · 167 citations
6. WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMsConference on Neural Information Processing Systems (NeurIPS)Seungju Han, Kavel Rao, Allyson Ettinger, et al.2024 · 165 citations
7. Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive AttacksarXiv:2404.02151Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion2024 · 118 citations
8. SORRY-Bench: Systematically Evaluating Large Language Model Safety RefusalarXiv:2406.14598Tinghao Xie, Xiangyu Qi, Yi Zeng, et al.2024 · 87 citations
9. Multi-VALUE: A Framework for Cross-Dialectal English NLPCaleb Ziems, William Held, Jingfeng Yang, et al.2023 · 76 citations
10. Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedbackarXiv:2303.05453Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.2023 · 57 citations
11. Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human PerceptionInternational Conference on Computational Linguistics (COLING)Luyang Lin, Lingzhi Wang, Jinsong Guo, et al.2025 · 44 citations
12. Introducing v0.5 of the AI Safety Benchmark from MLCommonsarXiv:2404.12241Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.2024 · 38 citations
13. Qwen3Guard Technical ReportarXiv:2510.14276Haiquan Zhao, Chenhan Yuan, Fei Huang, et al.2025 · 33 citations
14. An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language ModelsarXiv:2301.09211Saghar Hosseini, Hamid Palangi, Ahmed Hassan Awadallah2023 · 19 citations
15. TADA : Task Agnostic Dialect Adapters for EnglishFindings of the Association for Computational LinguisticsWilliam Held, Caleb Ziems, Diyi Yang2023 · 17 citations
16. Holistic Agent Leaderboard: The Missing Infrastructure for AI Agent EvaluationarXiv:2510.11977Sayash Kapoor, Benedikt Stroebl, Peter Kirgis, et al.2025 · 11 citations
17. AMALIA: A Fully Open Large Language Model for European PortugueseInternational Conference on Computational Processing of PortugueseAfonso Simplício, Gonçalo Vinagre, Miguel Moura Ramos, et al.2026 · 1 citation
18. RAFFLES: Reasoning-based Attribution of Faults for LLM SystemsConference of the European Chapter of the Association for Computational Linguistics (EACL)Chenyang Zhu, Spencer Hong, Jingyu Wu, et al.2026 · 1 citation
19. Action Boundary Blindness: When LLM Agents Cannot Tell Where One Action Ends and Another BeginsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhangyi Wang, Bingnan Yu, Jiexiang Xu, et al.2026
20. Agentic CLEAR: Automating Multi-Level Evaluation of LLM AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Asaf Yehudai, Lilach Eden, Michal Shmueli-Scheuer2026
21. Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training DebiasingFindings of the Association for Computational LinguisticsFilip Trhlík, Andrew Caines, Paula Buttery2026
22. Gender and Politeness Perception: A Novel Approach for Exploring Annotations DisagreementConference of the European Chapter of the Association for Computational Linguistics (EACL)Ahmad Aljanaideh2026
23. SEA-SafeguardBench: Culturally Grounded Safety Benchmark for Southeast Asian LanguagesFindings of the Association for Computational LinguisticsPanuthep Tasawong, Jian Gang Ngui, Alham Fikri Aji, et al.2026
24. TryggLLM: A Benchmark for Evaluating LLM Safety in NorwegianLanguage Resources and Evaluation Conference (LREC)Samia Touileb, Truls Pedersen, Isabell Stinessen Haugen2026

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