🔗 Who cites «Recipes for Safety in Open-domain Chatbots»

112 papers of our library cite it (of the 149,439 whose bibliographies we read) · 30 with a page here, the most cited first · ← back to «Recipes for Safety in Open-domain Chatbots»

1. Training language models to follow instructions with human feedbackarXiv:2203.02155Long Ouyang, Jeff Wu, Xu Jiang, et al.2022 · 10,224 citations
2. Llama 2: Open Foundation and Fine-Tuned Chat ModelsarXiv:2307.09288Hugo Touvron, Louis Martin, Kevin Stone, et al.2023 · 9,669 citations
3. TruthfulQA: Measuring How Models Mimic Human FalsehoodsAnnual Meeting of the Association for Computational Linguistics (ACL)Stephanie Lin, Jacob Hilton, Owain Evans2022 · 2,088 citations
4. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelsarXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5BvosjAarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.2022 · 1,756 citations
5. OPT: Open Pre-trained Transformer Language ModelsarXiv:2205.01068Susan Zhang, Stephen Roller, Naman Goyal, et al.2022 · 1,755 citations
6. LaMDA: Language Models for Dialog ApplicationsarXiv:2201.08239Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.2022 · 1,344 citations
7. Bias and Fairness in Large Language Models: A SurveyComputational LinguisticsIsabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.2023 · 1,082 citations
8. Constitutional AI: Harmlessness from AI FeedbackarXiv:2212.08073Yuntao Bai, Saurav Kadavath, Sandipan Kundu, et al.2022 · 1,028 citations
9. Jailbroken: How Does LLM Safety Training Fail?Conference on Neural Information Processing Systems (NeurIPS)Alexander Wei, Nika Haghtalab, Jacob Steinhardt2023 · 688 citations
10. GeDi: Generative Discriminator Guided Sequence GenerationFindings of the Association for Computational LinguisticsBen Krause, Akhilesh Deepak Gotmare, Bryan McCann, et al.2021 · 449 citations
11. Internet-Augmented Dialogue GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Mojtaba Komeili, Kurt Shuster, Jason Weston2022 · 354 citations
12. CodeRL: Mastering Code Generation through Pretrained Models and Deep Reinforcement LearningConference on Neural Information Processing Systems (NeurIPS)Hung Le, Yue Wang, Akhilesh Deepak Gotmare, et al.2022 · 297 citations
13. BlenderBot 3: a deployed conversational agent that continually learns to responsibly engagearXiv:2208.03188Kurt Shuster, Jing Xu, Mojtaba Komeili, et al.2022 · 241 citations
14. Challenges in Detoxifying Language ModelsFindings of the Association for Computational LinguisticsJohannes Welbl, Amelia Glaese, Jonathan Uesato, et al.2021 · 213 citations
15. AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
16. GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via CipherarXiv:2308.06463Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.2023 · 168 citations
17. ProsocialDialog: A Prosocial Backbone for Conversational AgentsConference on Empirical Methods in Natural Language Processing (EMNLP)Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.2022 · 152 citations
18. Detoxifying Language Models Risks Marginalizing Minority VoicesConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Albert Xu, Eshaan Pathak, Eric Wallace, et al.2021 · 137 citations
19. Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt CompletionFindings of the Association for Computational LinguisticsKurt Shuster, Mojtaba Komeili, Leonard Adolphs, et al.2022 · 132 citations
20. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
21. Pretraining Language Models with Human PreferencesarXiv:2302.08582Tomasz Korbak, Kejian Shi, Angelica Chen, et al.2023 · 121 citations
22. Certifying LLM Safety against Adversarial PromptingarXiv:2309.02705Aounon Kumar, Chirag Agarwal, Suraj Srinivas, et al.2023 · 113 citations
23. Defending Against Alignment-Breaking Attacks via Robustly Aligned LLMAnnual Meeting of the Association for Computational Linguistics (ACL)Bochuan Cao, Yuanpu Cao, Lu Lin, et al.2024 · 109 citations
24. On the Safety of Conversational Models: Taxonomy, Dataset, and BenchmarkFindings of the Association for Computational LinguisticsHao Sun, Guangxuan Xu, Jiawen Deng, et al.2022 · 102 citations
25. Language Generation Models Can Cause Harm: So What Can We Do About It? An Actionable SurveyConference of the European Chapter of the Association for Computational Linguistics (EACL)Sachin Kumar, Vidhisha Balachandran, Lucille Njoo, et al.2023 · 90 citations
26. Survey of Vulnerabilities in Large Language Models Revealed by Adversarial AttacksarXiv:2310.10844Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.2023 · 83 citations
27. OR-Bench: An Over-Refusal Benchmark for Large Language ModelsarXiv:2405.20947Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.2024 · 76 citations
28. Unveiling the Implicit Toxicity in Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Wen, Pei Ke, Hao Sun, et al.2023 · 72 citations
29. Rewarding Chatbots for Real-World Engagement with Millions of UsersarXiv:2303.06135Robert Irvine, Douglas Boubert, Vyas Raina, et al.2023 · 22 citations
30. MultiPragEval: Multilingual Pragmatic Evaluation of Large Language ModelsProceedings of the 2nd GenBench Workshop on Generalisation (Benchmarking) in NLPDojun Park, Jiwoo Lee, Seohyun Park, et al.2024 · 17 citations

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