🧑‍🔬 Who cites Peter Hase

403 citations of their works from 388 papers of our library (of the 141,840 whose bibliographies we read) · 27 with a page here, the most cited first · ← Peter Hase

1. On the Opportunities and Risks of Foundation ModelsRishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.2021 · 3,056 citations
2. A Survey of Large Language ModelsWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,863 citations
3. GLM-130B: An Open Bilingual Pre-trained ModelAohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 779 citations
4. Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought PromptingMiles Turpin, Julian Michael, Ethan Perez, et al.2023 · 568 citations
5. Do Prompt-Based Models Really Understand the Meaning of Their Prompts?Albert Webson, Ellie Pavlick2022 · 398 citations
6. Automatic Prompt Optimization with “Gradient Descent” and Beam SearchReid Pryzant, Dan Iter, Jerry Li, et al.2023 · 397 citations
7. Large Language Models as OptimizersChengrun Yang, Xuezhi Wang, Yifeng Lu, et al.2023 · 390 citations
8. RLPrompt: Optimizing Discrete Text Prompts with Reinforcement LearningMingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.2022 · 328 citations
9. Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving ModelsTongshuang Wu, Marco Tulio Ribeiro, Jeffrey Heer, et al.2021 · 272 citations
10. Ignore Previous Prompt: Attack Techniques For Language ModelsFabio Perez, Ian Ribeiro2022 · 245 citations
11. Measuring Association Between Labels and Free-Text RationalesSarah Wiegreffe, Ana Marasović, Noah A. Smith2021 · 215 citations
12. Towards Faithful Model Explanation in NLP: A SurveyQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 195 citations
13. The Prompt Report: A Systematic Survey of Prompt Engineering TechniquesSander Schulhoff, Michael Ilie, Nishant Balepur, et al.2024 · 187 citations
14. Knowledge Conflicts for LLMs: A SurveyRongwu Xu, Zehan Qi, Zhijiang Guo, et al.2024 · 179 citations
15. Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 174 citations
16. Quark: Controllable Text Generation with Reinforced UnlearningXiming Lu, Sean Welleck, Jack Hessel, et al.2022 · 165 citations
17. Language Models as Agent ModelsJacob Andreas2022 · 157 citations
18. SCOTT: Self-Consistent Chain-of-Thought DistillationPeifeng Wang, Zhengyang Wang, Zheng Li, et al.2023 · 145 citations
19. Prompting is not a substitute for probability measurements in large language modelsJennifer Hu, Roger Levy2023 · 133 citations
20. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
21. Leakage-Adjusted Simulatability: Can Models Generate Non-Trivial Explanations of Their Behavior in Natural Language?Peter Hase, Shiyue Zhang, Harry Xie, et al.2020 · 120 citations
22. Aligning Faithful Interpretations with their Social AttributionAlon Jacovi, Yoav Goldberg2021 · 119 citations
23. Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, et al.2022 · 107 citations
24. PRover: Proof Generation for Interpretable Reasoning over RulesSwarnadeep Saha, Sayan Ghosh, Shashank Srivastava, et al.2020 · 101 citations
25. Faithfulness Tests for Natural Language ExplanationsPepa Atanasova, Oana-Maria Camburu, Christina Lioma, et al.2023 · 92 citations
26. Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought ReasoningDebjit Paul, Robert West, Antoine Bosselut, et al.2024 · 77 citations
27. Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-TuningMing Li, Yong Zhang, Shwai He, et al.2024 · 60 citations

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