Who cites Roger Grosse
- GPT-4 Technical ReportarXiv:2303.08774OpenAI, Josh Achiam, Steven Adler, et al.2023 · 13,036 citations
- Unsupervised Representation Learning with Deep Convolutional Generative Adversarial NetworksarXiv:1511.06434Alec Radford, Luke Metz, Soumith Chintala2015 · 6,654 citations
- A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open QuestionsACM Transactions on Information SystemsLei Huang, Weijiang Yu, Weitao Ma, et al.2023 · 3,231 citations
- On the Opportunities and Risks of Foundation ModelsarXiv:2108.07258Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,160 citations
- ImageNet Classification with Deep Convolutional Neural NetworksNeurIPS 2012Alex Krizhevsky, Ilya Sutskever, Geoffrey E. Hinton2012 · 2,801 citations
- Measuring Mathematical Problem Solving With the MATH DatasetarXiv:2103.03874Dan Hendrycks, Collin Burns, Saurav Kadavath, et al.2021 · 2,395 citations
- Deep Unsupervised Learning using Nonequilibrium ThermodynamicsarXiv:1503.03585Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, et al.2015 · 1,761 citations
- The Concrete Distribution: A Continuous Relaxation of Discrete Random VariablesarXiv:1611.00712Chris J. Maddison, Andriy Mnih, Yee Whye Teh2016 · 1,629 citations
- GPQA: A Graduate-Level Google-Proof Q&A BenchmarkarXiv:2311.12022David Rein, Betty Li Hou, Asa Cooper Stickland, et al.2023 · 1,018 citations
- Solving Quantitative Reasoning Problems with Language ModelsConference on Neural Information Processing Systems (NeurIPS)Aitor Lewkowycz, Anders Andreassen, David Dohan, et al.2022 · 992 citations
- Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language ModelsComputational LinguisticsYue Zhang, Yafu Li, Leyang Cui, et al.2023 · 977 citations
- Explainability for Large Language Models: A SurveyACM Transactions on Intelligent Systems and TechnologyHaiyan Zhao, Hanjie Chen, Fan Yang, et al.2023 · 790 citations
- Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingConference on Neural Information Processing Systems (NeurIPS)Miles Turpin, Julian Michael, Ethan Perez, et al.2023 · 586 citations
- OpenAssistant Conversations — Democratizing Large Language Model AlignmentarXiv:2304.07327Andreas Köpf, Yannic Kilcher, Dimitri von Rütte, et al.2023 · 518 citations
- Inference-Time Intervention: Eliciting Truthful Answers from a Language ModelConference on Neural Information Processing Systems (NeurIPS)Kenneth Li, Oam Patel, Fernanda Viegas, et al.2023 · 492 citations
- In-context Learning and Induction HeadsarXiv:2209.11895Catherine Olsson, Nelson Elhage, Neel Nanda, et al.2022 · 475 citations
- AlpacaFarm: A Simulation Framework for Methods that Learn from Human FeedbackConference on Neural Information Processing Systems (NeurIPS)Yann Dubois, Xuechen Li, Rohan Taori, et al.2023 · 456 citations
- Whose Opinions Do Language Models Reflect?arXiv:2303.17548Shibani Santurkar, Esin Durmus, Faisal Ladhak, et al.2023 · 414 citations
- Editing Models with Task ArithmeticarXiv:2212.04089Gabriel Ilharco, Marco Tulio Ribeiro, Mitchell Wortsman, et al.2022 · 402 citations
- Representation Engineering: A Top-Down Approach to AI TransparencyarXiv:2310.01405Andy Zou, Long Phan, Sarah Chen, et al.2023 · 397 citations
- Towards Understanding Sycophancy in Language ModelsarXiv:2310.13548Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.2023 · 384 citations
- Representation Learning: A Review and New PerspectivesarXiv:1206.5538Yoshua Bengio, Aaron Courville, Pascal Vincent2012 · 383 citations
- Empowering Biomedical Discovery with AI AgentsarXiv:2404.02831Shanghua Gao, Ada Fang, Yepeng Huang, et al.2024 · 333 citations
- Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
- JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.2024 · 277 citations
- Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency AnalysisACM Computing Surveys 2019Tal Ben-Nun, Torsten Hoefler2018 · 275 citations
- Towards Measuring the Representation of Subjective Global Opinions in Language ModelsarXiv:2306.16388Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.2023 · 270 citations
- Automatic Text Scoring Using Neural NetworksAnnual Meeting of the Association for Computational Linguistics (ACL)Dimitrios Alikaniotis, Helen Yannakoudakis, Marek Rei2016 · 259 citations
- MiniF2F: a cross-system benchmark for formal Olympiad-level mathematicsarXiv:2109.00110Kunhao Zheng, Jesse Michael Han, Stanislas Polu2021 · 257 citations
- LeanDojo: Theorem Proving with Retrieval-Augmented Language ModelsConference on Neural Information Processing Systems (NeurIPS)Kaiyu Yang, Aidan M. Swope, Alex Gu, et al.2023 · 253 citations
- 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
- Generative Language Modeling for Automated Theorem ProvingarXiv:2009.03393Stanislas Polu, Ilya Sutskever2020 · 241 citations
- Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt InjectionarXiv:2302.12173Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.2023 · 239 citations
- TrustLLM: Trustworthiness in Large Language ModelsarXiv:2401.05561Yue Huang, Lichao Sun, Haoran Wang, et al.2024 · 237 citations
- Steering Language Models With Activation EngineeringarXiv:2308.10248Alexander Matt Turner, Lisa Thiergart, Gavin Leech, et al.2023 · 233 citations
- Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' AlignmentarXiv:2308.05374Yang Liu; Yuanshun Yao; Jean-Francois Ton; Xiaoying Zhang; Ruocheng Guo; Hao Cheng; Yegor Klochkov; Muhammad Faaiz Taufiq;, Hang Li2023 · 223 citations
- FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative FlowConference on Empirical Methods in Natural Language Processing (EMNLP)Xuezhe Ma, Chunting Zhou, Xian Li, et al.2019 · 218 citations
- Combating Misinformation in the Age of LLMs: Opportunities and ChallengesAI MagazineCanyu Chen, Kai Shu2023 · 214 citations
- Optimus: Organizing Sentences via Pre-trained Modeling of a Latent SpaceConference on Empirical Methods in Natural Language Processing (EMNLP)Chunyuan Li, Xiang Gao, Yuan Li, et al.2020 · 208 citations
- Autoformalization with Large Language ModelsarXiv:2205.12615Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.2022 · 204 citations
- Refusal in Language Models Is Mediated by a Single DirectionarXiv:2406.11717Andy Arditi, Oscar Obeso, Aaquib Syed, et al.2024 · 196 citations
- ELEPHANT: Measuring and understanding social sycophancy in LLMsScienceMyra Cheng, Sunny Yu, Cinoo Lee, et al.2025 · 188 citations
- Eliciting Latent Predictions from Transformers with the Tuned LensarXiv:2303.08112Nora Belrose, Igor Ostrovsky, Lev McKinney, et al.2023 · 188 citations
- Knowledge Conflicts for LLMs: A SurveyConference on Empirical Methods in Natural Language Processing (EMNLP)Rongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 182 citations
- Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 182 citations
- LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 179 citations
- LESS: Selecting Influential Data for Targeted Instruction TuningarXiv:2402.04333Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.2024 · 178 citations
- Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal ProofsarXiv:2210.12283Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, et al.2022 · 178 citations
- AI Alignment: A Comprehensive SurveyarXiv:2310.19852Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.2023 · 173 citations
- Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak SupervisionarXiv:2312.09390Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.2023 · 172 citations
- The Geometry of Truth: Emergent Linear Structure in Large Language Model Representations of True/False DatasetsarXiv:2310.06824Samuel Marks, Max Tegmark2023 · 169 citations
- The Linear Representation Hypothesis and the Geometry of Large Language ModelsInternational Conference on Machine Learning (ICML)Kiho Park, Yo Joong Choe, Victor Veitch2023 · 165 citations
- Abstraction and analogy-making in artificial intelligenceMelanie Mitchell2021 · 161 citations
- A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and TrustworthinessACM Transactions on Intelligent Systems and TechnologyFali Wang, Zhiwei Zhang, Xianren Zhang, et al.2024 · 159 citations
- Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
- A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 143 citations
- Exploring Length Generalization in Large Language ModelsarXiv:2207.04901Cem Anil, Yuhuai Wu, Anders Andreassen, et al.2022 · 139 citations
- SOTOPIA: Interactive Evaluation for Social Intelligence in Language AgentsarXiv:2310.11667Xuhui Zhou, Hao Zhu, Leena Mathur, et al.2023 · 138 citations
- Simple synthetic data reduces sycophancy in large language modelsarXiv:2308.03958Jerry Wei, Da Huang, Yifeng Lu, et al.2023 · 134 citations
- Formal Mathematics Statement Curriculum LearningarXiv:2202.01344Stanislas Polu, Jesse Michael Han, Kunhao Zheng, et al.2022 · 133 citations
- Improving Language Model Negotiation with Self-Play and In-Context Learning from AI FeedbackarXiv:2305.10142Yao Fu, Hao Peng, Tushar Khot, et al.2023 · 132 citations
- Scaling Deep Contrastive Learning Batch Size under Memory Limited SetupWorkshop on Representation Learning for NLPLuyu Gao, Yunyi Zhang, Jiawei Han, et al.2021 · 131 citations
- Evaluating the Moral Beliefs Encoded in LLMsConference on Neural Information Processing Systems (NeurIPS)Nino Scherrer, Claudia Shi, Amir Feder, et al.2023 · 129 citations
- Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 124 citations
- Sleeper Agents: Training Deceptive LLMs that Persist Through Safety TrainingarXiv:2401.05566Evan Hubinger, Carson Denison, Jesse Mu, et al.2024 · 123 citations
- Finding Neurons in a Haystack: Case Studies with Sparse ProbingarXiv:2305.01610Wes Gurnee, Neel Nanda, Matthew Pauly, et al.2023 · 123 citations
- The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
- A Latent Variable Recurrent Neural Network for Discourse-Driven Language ModelsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Yangfeng Ji, Gholamreza Haffari, Jacob Eisenstein2016 · 121 citations
- Best Practices and Lessons Learned on Synthetic DataarXiv:2404.07503Ruibo Liu, Jerry Wei, Fangyu Liu, et al.2024 · 119 citations
- Emergent Linear Representations in World Models of Self-Supervised Sequence ModelsarXiv:2309.00941Neel Nanda, Andrew Lee, Martin Wattenberg2023 · 116 citations
- Fundamental Limitations of Alignment in Large Language ModelsarXiv:2304.11082Yotam Wolf, Noam Wies, Oshri Avnery, et al.2023 · 114 citations
- DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic DataarXiv:2405.14333Huajian Xin, Daya Guo, Zhihong Shao, et al.2024 · 111 citations
- Mechanistic Interpretability for AI Safety — A ReviewarXiv:2404.14082Leonard Bereska, Efstratios Gavves2024 · 108 citations
- Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 105 citations
- Studying Large Language Model Generalization with Influence FunctionsarXiv:2308.03296Roger Grosse, Juhan Bae, Cem Anil, et al.2023 · 105 citations
- Model evaluation for extreme risksarXiv:2305.15324Toby Shevlane, Sebastian Farquhar, Ben Garfinkel, et al.2023 · 104 citations
- Debating with More Persuasive LLMs Leads to More Truthful AnswersarXiv:2402.06782Akbir Khan, John Hughes, Dan Valentine, et al.2024 · 101 citations
- FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
- R-Tuning: Instructing Large Language Models to Say ‘I Don't Know'Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hanning Zhang, Shizhe Diao, Yong Lin, et al.2024 · 99 citations
- Moral Foundations of Large Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Marwa Abdulhai, Gregory Serapio-García, Clement Crepy, et al.2024 · 94 citations
- WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 92 citations
- Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
- Rethinking Interpretability in the Era of Large Language ModelsarXiv:2402.01761Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.2024 · 87 citations
- Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language GenerationTransactions of the Association for Computational Linguistics (TACL)Patrick Fernandes, Aman Madaan, Emmy Liu, et al.2023 · 84 citations
- Testing the General Deductive Reasoning Capacity of Large Language Models Using OOD ExamplesConference on Neural Information Processing Systems (NeurIPS)Abulhair Saparov, Richard Yuanzhe Pang, Vishakh Padmakumar, et al.2023 · 84 citations
- PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human PreferenceAnnual Meeting of the Association for Computational Linguistics (ACL)Jiaming Ji, Donghai Hong, Borong Zhang, et al.2025 · 83 citations
- Proof Artifact Co-training for Theorem Proving with Language ModelsarXiv:2102.06203Jesse Michael Han, Jason Rute, Yuhuai Wu, et al.2021 · 82 citations
- Generating Benchmarks for Factuality Evaluation of Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Dor Muhlgay, Ori Ram, Inbal Magar, et al.2024 · 81 citations
- LEGO-Prover: Neural Theorem Proving with Growing LibrariesarXiv:2310.00656Haiming Wang, Huajian Xin, Chuanyang Zheng, et al.2023 · 79 citations
- Measuring Political Bias in Large Language Models: What Is Said and How It Is SaidAnnual Meeting of the Association for Computational Linguistics (ACL)Yejin Bang, Delong Chen, Nayeon Lee, et al.2024 · 76 citations
- NaturalProofs: Mathematical Theorem Proving in Natural LanguagearXiv:2104.01112Sean Welleck, Jiacheng Liu, Ronan Le Bras, et al.2021 · 76 citations
- ReFT: Representation Finetuning for Language ModelsConference on Neural Information Processing Systems (NeurIPS)Zhengxuan Wu, Aryaman Arora, Zheng Wang, et al.2024 · 74 citations
- Large Language Models as Analogical ReasonersarXiv:2310.01714Michihiro Yasunaga, Xinyun Chen, Yujia Li, et al.2023 · 74 citations
- A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
- Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-trainingarXiv:2305.14342Hong Liu, Zhiyuan Li, David Hall, et al.2023 · 70 citations
- OffsetBias: Leveraging Debiased Data for Tuning EvaluatorsFindings of the Association for Computational LinguisticsJunsoo Park, Seungyeon Jwa, Ren Meiying, et al.2024 · 67 citations
- ARB: Advanced Reasoning Benchmark for Large Language ModelsarXiv:2307.13692Tomohiro Sawada, Daniel Paleka, Alexander Havrilla, et al.2023 · 66 citations
- Linear Representations of Sentiment in Large Language ModelsarXiv:2310.15154Curt Tigges, Oskar John Hollinsworth, Atticus Geiger, et al.2023 · 64 citations
- Llama Scope: Extracting Millions of Features from Llama-3.1-8B with Sparse AutoencodersarXiv:2410.20526Zhengfu He, Wentao Shu, Xuyang Ge, et al.2024 · 63 citations
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