---
title: "Who cites Yangsibo Huang — 661 papers of our library"
description: "661 papers of the Elamur Research library cite the works of Yangsibo Huang, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Yangsibo Huang

769 citations of their works from 661 papers of our library (of the 149,439 whose bibliographies we read) · 177 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Yangsibo Huang](https://md.research.elamur.ai/free/en/authors/yangsibo-huang/)

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1. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/)
2. [**Jailbreaking Black Box Large Language Models in Twenty Queries arXiv:2310.08419**Patrick Chao, Alexander Robey, Edgar Dobriban, et al.*2023 · 553 citations*](https://md.research.elamur.ai/free/en/papers/chao-2023-jailbreaking-black-box-large-language/)
3. **[Security and Privacy Challenges of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/das-2024-security-privacy-challenges-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu*2024 · 424 citations*
4. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal arXiv:2402.04249**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 330 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/)
5. **[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*
6. [**TrustLLM: Trustworthiness in Large Language Models arXiv:2401.05561**Yue Huang, Lichao Sun, Haoran Wang, et al.*2024 · 237 citations*](https://md.research.elamur.ai/free/en/papers/huang-2024-trustllm-trustworthiness-large-language-models/)
7. **[Combating Misinformation in the Age of LLMs: Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/chen-2023-combating-misinformation-age-llms-opportunities/) [AI Magazine](https://md.research.elamur.ai/free/en/venues/ai-magazine/)**Canyu Chen, Kai Shu*2023 · 214 citations*
8. [**Refusal in Language Models Is Mediated by a Single Direction arXiv:2406.11717**Andy Arditi, Oscar Obeso, Aaquib Syed, et al.*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/arditi-2024-refusal-language-models-mediated-single/)
9. [**LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods arXiv:2412.05579**Haitao Li, Qian Dong, Junjie Chen, et al.*2024 · 195 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/)
10. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
11. **[Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models](https://md.research.elamur.ai/free/en/papers/chen-2025-towards-reasoning-era-survey-long/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Qiguang Chen, Libo Qin, Jinhao Liu, et al.*2025 · 176 citations*
12. [**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/)
13. [**GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher arXiv:2308.06463**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2023 · 168 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2023-gpt-4-too-smart-safe/)
14. [**SmoothLLM: Defending Large Language Models Against Jailbreaking Attacks arXiv:2310.03684**Alexander Robey, Eric Wong, Hamed Hassani, et al.*2023 · 164 citations*](https://md.research.elamur.ai/free/en/papers/robey-2023-smoothllm-defending-large-language-models/)
15. **[FigStep: Jailbreaking Large Vision-Language Models via Typographic Visual Prompts](https://md.research.elamur.ai/free/en/papers/gong-2023-figstep-jailbreaking-large-vision-language/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yichen Gong, Delong Ran, Jinyuan Liu, et al.*2023 · 163 citations*
16. **[A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness](https://md.research.elamur.ai/free/en/papers/wang-2024-comprehensive-survey-small-language-models/) [ACM Transactions on Intelligent Systems and Technology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-intelligent-systems-and-technology/)**Fali Wang, Zhiwei Zhang, Xianren Zhang, et al.*2024 · 159 citations*
17. **[MM-SafetyBench: A Benchmark for Safety Evaluation of Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2023-mm-safetybench-benchmark-safety-evaluation/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Xin Liu, Yichen Zhu, Jindong Gu, et al.*2023 · 152 citations*
18. [**The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning arXiv:2312.01552**Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, et al.*2023 · 150 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-unlocking-spell-base-llms-rethinking/)
19. [**TOFU: A Task of Fictitious Unlearning for LLMs arXiv:2401.06121**Pratyush Maini, Zhili Feng, Avi Schwarzschild, et al.*2024 · 144 citations*](https://md.research.elamur.ai/free/en/papers/maini-2024-tofu-task-fictitious-unlearning-llms/)
20. [**DeepInception: Hypnotize Large Language Model to Be Jailbreaker arXiv:2311.03191**Xuan Li, Zhanke Zhou, Jianing Zhu, et al.*2023 · 141 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-deepinception-hypnotize-large-language-model/)
21. **[Investigating Data Contamination in Modern Benchmarks for Large Language Models](https://md.research.elamur.ai/free/en/papers/deng-2024-investigating-data-contamination-modern-benchmarks/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Chunyuan Deng, Yilun Zhao, Xiangru Tang, et al.*2024 · 137 citations*
22. [**RAFT: Adapting Language Model to Domain Specific RAG arXiv:2403.10131**Tianjun Zhang, Shishir G. Patil, Naman Jain, et al.*2024 · 137 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/)
23. **[The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization](https://md.research.elamur.ai/free/en/papers/pilan-2022-text-anonymization-benchmark-tab-dedicated/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Ildikó Pilán, Pierre Lison, Lilja Øvrelid, et al.*2022 · 131 citations*
24. [**Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations arXiv:2310.06387**Zeming Wei, Yifei Wang, Ang Li, et al.*2023 · 130 citations*](https://md.research.elamur.ai/free/en/papers/wei-2023-jailbreak-guard-aligned-language-models/)
25. **[SafeDecoding: Defending against Jailbreak Attacks via Safety-Aware Decoding](https://md.research.elamur.ai/free/en/papers/xu-2024-safedecoding-defending-against-jailbreak-attacks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhangchen Xu, Fengqing Jiang, Luyao Niu, et al.*2024 · 127 citations*
26. [**Negative Preference Optimization: From Catastrophic Collapse to Effective Unlearning arXiv:2404.05868**Ruiqi Zhang, Licong Lin, Yu Bai, et al.*2024 · 126 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-negative-preference-optimization-catastrophic-collapse/)
27. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
28. [**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/)
29. **[SALAD-Bench: A Hierarchical and Comprehensive Safety Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-salad-bench-hierarchical-comprehensive-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lijun Li, Bowen Dong, Ruohui Wang, et al.*2024 · 119 citations*
30. **[LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/zhang-2025-lmms-eval-reality-check-evaluation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaichen Zhang, Bo Li, Peiyuan Zhang, et al.*2025 · 115 citations*
31. [**Don't Make Your LLM an Evaluation Benchmark Cheater arXiv:2311.01964**Kun Zhou, Yutao Zhu, Zhipeng Chen, et al.*2023 · 112 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2023-don-t-make-llm-evaluation/)
32. **[A Systematic Survey and Critical Review on Evaluating Large Language Models: Challenges, Limitations, and Recommendations](https://md.research.elamur.ai/free/en/papers/laskar-2024-systematic-survey-critical-review-evaluating/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Md Tahmid Rahman Laskar, Sawsan Alqahtani, M Saiful Bari, et al.*2024 · 105 citations*
33. [**Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning arXiv:2502.14768**Tian Xie, Zitian Gao, Qingnan Ren, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/xie-2025-logic-rl-unleashing-llm/)
34. [**REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization arXiv:2501.03262**Jian Hu, Jason Klein Liu, Haotian Xu, et al.*2025 · 104 citations*](https://md.research.elamur.ai/free/en/papers/hu-2025-reinforce-stabilizing-critic-free-policy/)
35. [**Rethinking Benchmark and Contamination for Language Models with Rephrased Samples arXiv:2311.04850**Shuo Yang, Wei-Lin Chiang, Lianmin Zheng, et al.*2023 · 103 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-rethinking-benchmark-contamination-language-models/)
36. **[A Careful Examination of Large Language Model Performance on Grade School Arithmetic](https://md.research.elamur.ai/free/en/papers/zhang-2024-careful-examination-large-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Hugh Zhang, Jeff Da, Dean Lee, et al.*2024 · 101 citations*
37. **[MathArena: Evaluating LLMs on Uncontaminated Math Competitions](https://md.research.elamur.ai/free/en/papers/balunovic-2025-matharena-evaluating-llms-uncontaminated-math/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Mislav Balunović, Jasper Dekoninck, Ivo Petrov, et al.*2025 · 99 citations*
38. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
39. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
40. **[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*
41. [**AutoDAN: Interpretable Gradient-Based Adversarial Attacks on Large Language Models arXiv:2310.15140**Sicheng Zhu, Ruiyi Zhang, Bang An, et al.*2023 · 90 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-autodan-interpretable-gradient-based-adversarial/)
42. [**Do Membership Inference Attacks Work on Large Language Models? arXiv:2402.07841**Michael Duan, Anshuman Suri, Niloofar Mireshghallah, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/duan-2024-membership-inference-attacks-work-large/)
43. [**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/)
44. [**SORRY-Bench: Systematically Evaluating Large Language Model Safety Refusal arXiv:2406.14598**Tinghao Xie, Xiangyu Qi, Yi Zeng, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/xie-2024-sorry-bench-systematically-evaluating-large/)
45. **[Is LLM-as-a-Judge Robust? Investigating Universal Adversarial Attacks on Zero-shot LLM Assessment](https://md.research.elamur.ai/free/en/papers/raina-2024-is-llm-as-judge-robust/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Vyas Raina, Adian Liusie, Mark Gales*2024 · 86 citations*
46. **[Machine Unlearning of Pre-trained Large Language Models](https://md.research.elamur.ai/free/en/papers/yao-2024-machine-unlearning-pre-trained-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Yao, Eli Chien, Minxin Du, et al.*2024 · 86 citations*
47. [**Benchmark Data Contamination of Large Language Models: A Survey arXiv:2406.04244**Cheng Xu, Shuhao Guan, Derek Greene, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmark-data-contamination-large/)
48. [**On Prompt-Driven Safeguarding for Large Language Models arXiv:2401.18018**Chujie Zheng, Fan Yin, Hao Zhou, et al.*2024 · 85 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2024-prompt-driven-safeguarding-large-language/)
49. **[Detoxifying Large Language Models via Knowledge Editing](https://md.research.elamur.ai/free/en/papers/wang-2024-detoxifying-large-language-models-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mengru Wang, Ningyu Zhang, Ziwen Xu, et al.*2024 · 84 citations*
50. [**PoisonedRAG: Knowledge Corruption Attacks to Retrieval-Augmented Generation of Large Language Models arXiv:2402.07867**Wei Zou, Runpeng Geng, Binghui Wang, et al.*2024 · 80 citations*](https://md.research.elamur.ai/free/en/papers/zou-2024-poisonedrag-knowledge-corruption-attacks-retrieval/)
51. [**SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-Scaling arXiv:2312.15166**Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.*2023 · 77 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-solar-10-7b-scaling-large/)
52. [**OR-Bench: An Over-Refusal Benchmark for Large Language Models arXiv:2405.20947**Justin Cui, Wei-Lin Chiang, Ion Stoica, et al.*2024 · 76 citations*](https://md.research.elamur.ai/free/en/papers/cui-2024-bench-over-refusal-benchmark-large/)
53. [**INCLUDE: Evaluating Multilingual Language Understanding with Regional Knowledge arXiv:2411.19799**Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.*2024 · 74 citations*](https://md.research.elamur.ai/free/en/papers/romanou-2024-include-evaluating-multilingual-language-understanding/)
54. [**Benchmarking Benchmark Leakage in Large Language Models arXiv:2404.18824**Ruijie Xu, Zengzhi Wang, Run-Ze Fan, et al.*2024 · 73 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-benchmarking-benchmark-leakage-large-language/)
55. [**Great, Now Write an Article About That: The Crescendo Multi-Turn LLM Jailbreak Attack arXiv:2404.01833**Mark Russinovich, Ahmed Salem, Ronen Eldan*2024 · 71 citations*](https://md.research.elamur.ai/free/en/papers/russinovich-2024-great-now-write-article-about/)
56. **[Self-Alignment for Factuality: Mitigating Hallucinations in LLMs via Self-Evaluation](https://md.research.elamur.ai/free/en/papers/zhang-2024-self-alignment-factuality-mitigating-hallucinations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoying Zhang, Baolin Peng, Ye Tian, et al.*2024 · 69 citations*
57. [**Assessing the Brittleness of Safety Alignment via Pruning and Low-Rank Modifications arXiv:2402.05162**Boyi Wei, Kaixuan Huang, Yangsibo Huang, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/wei-2024-assessing-brittleness-safety-alignment-pruning/)
58. [**JailBreakV: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks arXiv:2404.03027**Weidi Luo, Siyuan Ma, Xiaogeng Liu, et al.*2024 · 66 citations*](https://md.research.elamur.ai/free/en/papers/luo-2024-jailbreakv-benchmark-assessing-robustness-multimodal/)
59. [**ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning arXiv:2502.01100**Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, et al.*2025 · 60 citations*](https://md.research.elamur.ai/free/en/papers/lin-2025-zebralogic-scaling-limits-llms-logical/)
60. **[SOUL: Unlocking the Power of Second-Order Optimization for LLM Unlearning](https://md.research.elamur.ai/free/en/papers/jia-2024-soul-unlocking-power-second-order/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jinghan Jia, Yihua Zhang, Yimeng Zhang, et al.*2024 · 46 citations*
61. **[On Memorization of Large Language Models in Logical Reasoning](https://md.research.elamur.ai/free/en/papers/xie-2025-memorization-large-language-models-logical/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Chulin Xie, Yangsibo Huang, Chiyuan Zhang, et al.*2025 · 45 citations*
62. **[Do Language Models Enjoy Their Own Stories? Prompting Large Language Models for Automatic Story Evaluation](https://md.research.elamur.ai/free/en/papers/chhun-2024-do-language-models-enjoy-their/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Cyril Chhun, Fabian M. Suchanek, Chloé Clavel*2024 · 41 citations*
63. **[Towards Robust Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/luong-2025-robust-mathematical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thang Luong, Dawsen Hwang, Hoang H Nguyen, et al.*2025 · 40 citations*
64. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
65. **[Benchmark Self-Evolving: A Multi-Agent Framework for Dynamic LLM Evaluation](https://md.research.elamur.ai/free/en/papers/wang-2025-benchmark-self-evolving-multi-agent/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Siyuan Wang, Zhuohan Long, Zhihao Fan, et al.*2025 · 30 citations*
66. **[The Hidden Risks of Large Reasoning Models: A Safety Assessment of R1](https://md.research.elamur.ai/free/en/papers/zhou-2025-hidden-risks-large-reasoning-models/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Kaiwen Zhou, Chengzhi Liu, Xuandong Zhao, et al.*2025 · 30 citations*
67. **[Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification](https://md.research.elamur.ai/free/en/papers/zhang-2025-breaking-agents-compromising-autonomous-llm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Boyang Zhang, Yicong Tan, Yun Shen, et al.*2025 · 29 citations*
68. [**Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming arXiv:2501.18837**Mrinank Sharma, Meg Tong, Jesse Mu, et al.*2025 · 29 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2025-constitutional-classifiers-defending-against-universal/)
69. **[ErrorRadar: Benchmarking Complex Mathematical Reasoning of Multimodal Large Language Models Via Error Detection](https://md.research.elamur.ai/free/en/papers/yan-2026-errorradar-benchmarking-complex-mathematical-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yibo Yan, Shen Wang, Jiahao Huo, et al.*2026 · 23 citations*
70. [**Source-Aware Training Enables Knowledge Attribution in Language Models arXiv:2404.01019**Muhammad Khalifa, David Wadden, Emma Strubell, et al.*2024 · 21 citations*](https://md.research.elamur.ai/free/en/papers/khalifa-2024-source-aware-training-enables-knowledge/)
71. **[Benchmarking LLMs for Translating Classical Chinese Poetry: Evaluating Adequacy, Fluency, and Elegance](https://md.research.elamur.ai/free/en/papers/chen-2025-benchmarking-llms-translating-classical-chinese/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Andong Chen, Lianzhang Lou, Kehai Chen, et al.*2025 · 18 citations*
72. **[Understanding Jailbreak Success: A Study of Latent Space Dynamics in Large Language Models](https://md.research.elamur.ai/free/en/papers/ball-2026-understanding-jailbreak-success-study-latent/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sarah Ball, Frauke Kreuter, Nina Panickssery*2026 · 17 citations*
73. **[Revisiting Jailbreaking for Large Language Models: A Representation Engineering Perspective](https://md.research.elamur.ai/free/en/papers/li-2025-revisiting-jailbreaking-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianlong Li, Zhenghua Wang, Wenhao Liu, et al.*2025 · 17 citations*
74. **[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*
75. **[Language Mixing in Reasoning Language Models: Patterns, Impact, and Internal Causes](https://md.research.elamur.ai/free/en/papers/wang-2025-language-mixing-reasoning-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingyang Wang, Lukas Lange, Heike Adel, et al.*2025 · 16 citations*
76. **[Towards Data Contamination Detection for Modern Large Language Models: Limitations, Inconsistencies, and Oracle Challenges](https://md.research.elamur.ai/free/en/papers/samuel-2025-data-contamination-detection-modern-large/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Vinay Samuel, Yue Zhou, Henry Peng Zou*2025 · 16 citations*
77. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
78. **[Learning to Refuse: Towards Mitigating Privacy Risks in LLMs](https://md.research.elamur.ai/free/en/papers/liu-2025-learning-refuse-mitigating-privacy-risks/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhenhua Liu, Tong Zhu, Chuanyuan Tan, et al.*2025 · 13 citations*
79. **[Safer or Luckier? LLMs as Safety Evaluators Are Not Robust to Artifacts](https://md.research.elamur.ai/free/en/papers/chen-2025-safer-or-luckier-llms-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hongyu Chen, Seraphina Goldfarb-Tarrant*2025 · 13 citations*
80. **[Safety Alignment via Constrained Knowledge Unlearning](https://md.research.elamur.ai/free/en/papers/shi-2025-safety-alignment-constrained-knowledge-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zesheng Shi, Yucheng Zhou, Jing Li, et al.*2025 · 13 citations*
81. **[Modality-Aware Neuron Pruning for Unlearning in Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/liu-2025-modality-aware-neuron-pruning-unlearning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheyuan Liu, Guangyao Dou, Xiangchi Yuan, et al.*2025 · 12 citations*
82. **[TripleFact: Defending Data Contamination in the Evaluation of LLM-driven Fake News Detection](https://md.research.elamur.ai/free/en/papers/xu-2025-triplefact-defending-data-contamination-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Cheng Xu, Nan Yan*2025 · 12 citations*
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87. **[Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2026-locate-steer-improve-practical-survey/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Hengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.*2026 · 9 citations*
88. [**Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment arXiv:2501.13080**Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/rad-2025-refining-input-guardrails-enhancing-llm/)
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90. **[Get Confused Cautiously: Textual Sequence Memorization Erasure with Selective Entropy Maximization](https://md.research.elamur.ai/free/en/papers/zhang-2025-get-confused-cautiously-textual-sequence/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhaohan Zhang, Ziquan Liu, Ioannis Patras*2025 · 7 citations*
91. **[SVELA at EVALITA 2026: Overview of the Selective Verification of Erasure from LLM Answers Task](https://md.research.elamur.ai/free/en/papers/savelli-2026-svela-evalita-2026-overview-selective/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Claudio Savelli, Moreno La Quatra, Alkis Koudounas, et al.*2026 · 6 citations*
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93. **[False Sense of Security: Why Probing-based Malicious Input Detection Fails to Generalize](https://md.research.elamur.ai/free/en/papers/wang-2026-false-sense-security-why-probing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Cheng Wang, Zeming Wei, Qin Liu, et al.*2026 · 5 citations*
94. **[Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning Models](https://md.research.elamur.ai/free/en/papers/guo-2026-mathematical-proof-as-litmus-test/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dadi Guo, Jiayu Liu, Zhiyuan Fan, et al.*2026 · 5 citations*
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98. **[BLUR: A Bi-Level Optimization Approach for LLM Unlearning](https://md.research.elamur.ai/free/en/papers/reisizadeh-2026-blur-bi-level-optimization-approach/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Hadi Reisizadeh, Jinghan Jia, Zhiqi Bu, et al.*2026 · 4 citations*
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100. **[Why LLM Safety Guardrails Collapse After Fine-tuning: A Similarity Analysis Between Alignment and Fine-tuning Datasets](https://md.research.elamur.ai/free/en/papers/hsiung-2026-why-llm-safety-guardrails-collapse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lei Hsiung, Tianyu Pang, Yung-Chen Tang, et al.*2026 · 4 citations*

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