---
title: "Who cites Daniel M. Ziegler — 223 papers of our library"
description: "223 papers of the Elamur Research library cite the works of Daniel M. Ziegler, found in their bibliographies; the most cited first."
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---
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# Who cites Daniel M. Ziegler

226 citations of their works from 223 papers of our library (of the 149,439 whose bibliographies we read) · 66 with a page here, the most cited first · [← Daniel M. Ziegler](https://md.research.elamur.ai/free/en/authors/daniel-m-ziegler/)

1. [**Training language models to follow instructions with human feedback arXiv:2203.02155**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 10,224 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
2. [**Finetuned Language Models Are Zero-Shot Learners arXiv:2109.01652**Jason Wei, Maarten Bosma, Vincent Y. Zhao, et al.*2021 · 1,954 citations*](https://md.research.elamur.ai/free/en/papers/wei-2021-finetuned-language-models-zero-shot/)
3. **[Red Teaming Language Models with Language Models](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 700 citations*
4. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
5. [**Improving alignment of dialogue agents via targeted human judgements arXiv:2209.14375**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 362 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
6. [**Solving math word problems with process- and outcome-based feedback arXiv:2211.14275**Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.*2022 · 355 citations*](https://md.research.elamur.ai/free/en/papers/uesato-2022-solving-math-word-problems-process/)
7. [**AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models arXiv:2310.04451**Xiaogeng Liu, Nan Xu, Muhao Chen, et al.*2023 · 350 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-autodan-generating-stealthy-jailbreak-prompts/)
8. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
9. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
10. **[JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/chao-2024-jailbreakbench-open-robustness-benchmark-jailbreaking/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Patrick Chao, Edoardo Debenedetti, Alexander Robey, et al.*2024 · 277 citations*
11. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment arXiv:2304.06767**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
12. [**Reinforced Self-Training (ReST) for Language Modeling arXiv:2308.08998**Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, et al.*2023 · 224 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2023-reinforced-self-training-rest-language/)
13. [**Fine-Grained Human Feedback Gives Better Rewards for Language Model Training arXiv:2306.01693**Zeqiu Wu, Yushi Hu, Weijia Shi, et al.*2023 · 223 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-fine-grained-human-feedback-gives/)
14. **[Aya Dataset: An Open-Access Collection for Multilingual Instruction Tuning](https://md.research.elamur.ai/free/en/papers/singh-2024-aya-dataset-open-access-collection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shivalika Singh, Freddie Vargus, Daniel D'souza, et al.*2024 · 207 citations*
15. [**RRHF: Rank Responses to Align Language Models with Human Feedback without tears arXiv:2304.05302**Zheng Yuan, Hongyi Yuan, Chuanqi Tan, et al.*2023 · 201 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-rrhf-rank-responses-align-language/)
16. [**RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval arXiv:2401.18059**Parth Sarthi, Salman Abdullah, Aditi Tuli, et al.*2024 · 193 citations*](https://md.research.elamur.ai/free/en/papers/sarthi-2024-raptor-recursive-abstractive-processing-tree/)
17. [**Is Reinforcement Learning (Not) for Natural Language Processing: Benchmarks, Baselines, and Building Blocks for Natural Language Policy Optimization arXiv:2210.01241**Rajkumar Ramamurthy, Prithviraj Ammanabrolu, Kiante Brantley, et al.*2022 · 174 citations*](https://md.research.elamur.ai/free/en/papers/ramamurthy-2022-reinforcement-learning-natural-language-processing/)
18. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
19. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
20. **[LooGLE: Can Long-Context Language Models Understand Long Contexts?](https://md.research.elamur.ai/free/en/papers/li-2023-loogle-long-context-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiaqi Li, Mengmeng Wang, Zilong Zheng, et al.*2023 · 165 citations*
21. [**SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents arXiv:2310.11667**Xuhui Zhou, Hao Zhu, Leena Mathur, et al.*2023 · 138 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-sotopia-interactive-evaluation-social-intelligence/)
22. [**The Alignment Problem from a Deep Learning Perspective arXiv:2209.00626**Richard Ngo, Lawrence Chan, Soren Mindermann*2022 · 121 citations*](https://md.research.elamur.ai/free/en/papers/ngo-2022-alignment-problem-deep-learning-perspective/)
23. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
24. [**Measuring Progress on Scalable Oversight for Large Language Models arXiv:2211.03540**Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2022-measuring-progress-scalable-oversight-large/)
25. [**RLHF Workflow: From Reward Modeling to Online RLHF arXiv:2405.07863**Hanze Dong, Wei Xiong, Bo Pang, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-rlhf-workflow-reward-modeling-online/)
26. **[GPTAraEval: A Comprehensive Evaluation of ChatGPT on Arabic NLP](https://md.research.elamur.ai/free/en/papers/khondaker-2023-gptaraeval-comprehensive-evaluation-chatgpt-arabic/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, et al.*2023 · 110 citations*
27. [**Mechanistic Interpretability for AI Safety — A Review arXiv:2404.14082**Leonard Bereska, Efstratios Gavves*2024 · 108 citations*](https://md.research.elamur.ai/free/en/papers/bereska-2024-mechanistic-interpretability-ai-safety-review/)
28. [**BooookScore: A systematic exploration of book-length summarization in the era of LLMs arXiv:2310.00785**Yapei Chang, Kyle Lo, Tanya Goyal, et al.*2023 · 108 citations*](https://md.research.elamur.ai/free/en/papers/chang-2023-booookscore-systematic-exploration-book-length/)
29. [**Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging arXiv:2310.11564**Joel Jang, Seungone Kim, Bill Yuchen Lin, et al.*2023 · 102 citations*](https://md.research.elamur.ai/free/en/papers/jang-2023-personalized-soups-personalized-large-language/)
30. [**Debating with More Persuasive LLMs Leads to More Truthful Answers arXiv:2402.06782**Akbir Khan, John Hughes, Dan Valentine, et al.*2024 · 101 citations*](https://md.research.elamur.ai/free/en/papers/khan-2024-debating-more-persuasive-llms-leads/)
31. [**Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-Constraint arXiv:2312.11456**Wei Xiong, Hanze Dong, Chenlu Ye, et al.*2023 · 100 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2023-iterative-preference-learning-human-feedback/)
32. **[WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-wildteaming-scale-wild-jailbreaks-adversarially/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Liwei Jiang, Kavel Rao, Seungju Han, et al.*2024 · 92 citations*
33. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
34. **[AutoSurvey: Large Language Models Can Automatically Write Surveys](https://md.research.elamur.ai/free/en/papers/wang-2024-autosurvey-large-language-models-automatically/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yidong Wang, Qi Guo, Wenjin Yao, et al.*2024 · 91 citations*
35. **[Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards](https://md.research.elamur.ai/free/en/papers/rame-2023-rewarded-soups-towards-pareto-optimal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alexandre Rame, Guillaume Couairon, Mustafa Shukor, et al.*2023 · 90 citations*
36. **[How to Train Long-Context Language Models (Effectively)](https://md.research.elamur.ai/free/en/papers/gao-2025-how-train-long-context-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Gao, Alexander Wettig, Howard Yen, et al.*2025 · 89 citations*
37. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
38. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
39. **[Mitigating the Alignment Tax of RLHF](https://md.research.elamur.ai/free/en/papers/lin-2024-mitigating-alignment-tax-rlhf/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yong Lin, Hangyu Lin, Wei Xiong, et al.*2024 · 83 citations*
40. [**MARG: Multi-Agent Review Generation for Scientific Papers arXiv:2401.04259**Mike D'Arcy, Tom Hope, Larry Birnbaum, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/arcy-2024-marg-multi-agent-review/)
41. **[Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback](https://md.research.elamur.ai/free/en/papers/roit-2023-factually-consistent-summarization-reinforcement-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Roit, Johan Ferret, Lior Shani, et al.*2023 · 70 citations*
42. **[OffsetBias: Leveraging Debiased Data for Tuning Evaluators](https://md.research.elamur.ai/free/en/papers/park-2024-offsetbias-leveraging-debiased-data-tuning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Junsoo Park, Seungyeon Jwa, Ren Meiying, et al.*2024 · 67 citations*
43. **[MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance](https://md.research.elamur.ai/free/en/papers/pi-2024-mllm-protector-ensuring-mllm-s/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Pi, Tianyang Han, Jianshu Zhang, et al.*2024 · 58 citations*
44. [**Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback arXiv:2303.05453**Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.*2023 · 57 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-personalisation-within-bounds-risk-taxonomy/)
45. [**A Human-Inspired Reading Agent with Gist Memory of Very Long Contexts arXiv:2402.09727**Kuang-Huei Lee, Xinyun Chen, Hiroki Furuta, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/lee-2024-human-inspired-reading-agent-gist/)
46. [**Introducing v0.5 of the AI Safety Benchmark from MLCommons arXiv:2404.12241**Bertie Vidgen, Adarsh Agrawal, Ahmed M. Ahmed, et al.*2024 · 38 citations*](https://md.research.elamur.ai/free/en/papers/vidgen-2024-introducing-v0-5-ai-safety/)
47. **[JASMINE: Arabic GPT Models for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/nagoudi-2023-jasmine-arabic-gpt-models-few/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, et al.*2023 · 38 citations*
48. [**BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models arXiv:2309.06085**Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, et al.*2023 · 33 citations*](https://md.research.elamur.ai/free/en/papers/leong-2023-bhasa-holistic-southeast-asian-linguistic/)
49. **[Reading Subtext: Evaluating Large Language Models on Short Story Summarization with Writers](https://md.research.elamur.ai/free/en/papers/subbiah-2024-reading-subtext-evaluating-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Melanie Subbiah, Sean Zhang, Lydia B. Chilton, et al.*2024 · 30 citations*
50. **[Language Models in Dialogue: Conversational Maxims for Human-AI Interactions](https://md.research.elamur.ai/free/en/papers/miehling-2024-language-models-dialogue-conversational-maxims/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Erik Miehling, Manish Nagireddy, Prasanna Sattigeri, et al.*2024 · 23 citations*
51. **[DARG: Dynamic Evaluation of Large Language Models via Adaptive Reasoning Graph](https://md.research.elamur.ai/free/en/papers/zhang-2024-darg-dynamic-evaluation-large-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Zhehao Zhang, Jiaao Chen, Diyi Yang*2024 · 17 citations*
52. **[Mitigating Lost-in-Retrieval Problems in Retrieval Augmented Multi-Hop Question Answering](https://md.research.elamur.ai/free/en/papers/zhu-2025-mitigating-lost-retrieval-problems-retrieval/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rongzhi Zhu, Xiangyu Liu, Zequn Sun, et al.*2025 · 16 citations*
53. [**TigerBot: An Open Multilingual Multitask LLM arXiv:2312.08688**Ye Chen, Wei Cai, Liangmin Wu, et al.*2023 · 15 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-tigerbot-open-multilingual-multitask/)
54. **[WildFeedback: Aligning LLMs With In-situ User Interactions And Feedback](https://md.research.elamur.ai/free/en/papers/shi-2026-wildfeedback-aligning-llms-situ-user/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taiwei Shi, Zhuoer Wang, Longqi Yang, et al.*2026 · 9 citations*
55. **[Agent-as-Judge for Factual Summarization of Long Narratives](https://md.research.elamur.ai/free/en/papers/jeong-2025-agent-as-judge-factual-summarization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yeonseok Jeong, Minsoo Kim, Seung-won Hwang, et al.*2025 · 8 citations*
56. **[Preconditioned Test-Time Adaptation for Out-of-Distribution Debiasing in Narrative Generation](https://md.research.elamur.ai/free/en/papers/shen-2026-preconditioned-test-time-adaptation-out/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanwen Shen, Ting Ying, Jiajie Lu, et al.*2026 · 2 citations*
57. **[AbLit: A Resource for Analyzing and Generating Abridged Versions of English Literature](https://md.research.elamur.ai/free/en/papers/roemmele-2023-ablit-resource-analyzing-generating-abridged/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Melissa Roemmele, Kyle Shaffer, Katrina Olsen, et al.*2023 · 2 citations*
58. **[Compiling Activation Steering into Weights via Null-Space Constraints for Stealthy Backdoors](https://md.research.elamur.ai/free/en/papers/yin-2026-compiling-activation-steering-into-weights/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Yin, Tianxu Han, Naen Xu, et al.*2026 · 1 citation*
59. **[PARASITE: Conditional System Prompt Poisoning to Hijack LLMs](https://md.research.elamur.ai/free/en/papers/pham-2026-parasite-conditional-system-prompt-poisoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Viet Pham, Thai Le*2026 · 1 citation*
60. [**HAMSA: Hijacking Aligned Compact Models via Stealthy Automation arXiv:2508.16484**Alexey Krylov, Iskander Vagizov, Dmitrii Korzh, et al.*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/krylov-2025-hamsa-hijacking-aligned-compact-models/)
61. **[DART: Mitigating Harm Drift in Difference-Aware LLMs via Distill-Audit-Repair Training](https://md.research.elamur.ai/free/en/papers/pan-2026-dart-mitigating-harm-drift-difference/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwen Pan, Zihan Liang, Jad Kabbara, et al.*2026*
62. **[Probing the Plasticity and Correlation of LLM Value Systems: LLM Value Rankings are Not Stable](https://md.research.elamur.ai/free/en/papers/tang-2026-probing-plasticity-correlation-llm-value/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhenheng Tang, Qihua Pan, Jingya Shen, et al.*2026*
63. **[RepoDistill: Distilling Repository Knowledge through Compression-Aware Budget Allocation and Policy Optimization](https://md.research.elamur.ai/free/en/papers/yin-2026-repodistill-distilling-repository-knowledge-through/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xin Yin, Zixiang Ding, Yiang Zhang, et al.*2026*
64. **[Think Before you Write: QA-Guided Reasoning for Character Descriptions in Books](https://md.research.elamur.ai/free/en/papers/papoudakis-2026-think-before-you-write-qa/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Argyrios Papoudakis, Mirella Lapata, Frank Keller*2026*
65. **[Understanding Emergent Misalignment via Feature Superposition Geometry](https://md.research.elamur.ai/free/en/papers/minegishi-2026-understanding-emergent-misalignment-feature-superposition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gouki Minegishi, Hiroki Furuta, Takeshi Kojima, et al.*2026*
66. [**360Zhinao Technical Report arXiv:2405.13386***2024*](https://md.research.elamur.ai/free/en/papers/360zhinao-team-2024-360zhinao-technical-report/)

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