---
title: "Who cites Ashwinee Panda — 190 papers of our library"
description: "190 papers of the Elamur Research library cite the works of Ashwinee Panda, found in their bibliographies; the most cited first."
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---
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# Who cites Ashwinee Panda

194 citations of their works from 190 papers of our library (of the 149,439 whose bibliographies we read) · 71 with a page here, the most cited first · [← Ashwinee Panda](https://md.research.elamur.ai/free/en/authors/ashwinee-panda/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
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. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
5. [**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/)
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. [**Baseline Defenses for Adversarial Attacks Against Aligned Language Models arXiv:2309.00614**Neel Jain, Avi Schwarzschild, Yuxin Wen, et al.*2023 · 236 citations*](https://md.research.elamur.ai/free/en/papers/jain-2023-baseline-defenses-adversarial-attacks-against/)
8. **[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*
9. [**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/)
10. [**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/)
11. [**Jailbreaking Leading Safety-Aligned LLMs with Simple Adaptive Attacks arXiv:2404.02151**Maksym Andriushchenko, Francesco Croce, Nicolas Flammarion*2024 · 118 citations*](https://md.research.elamur.ai/free/en/papers/andriushchenko-2024-jailbreaking-leading-safety-aligned-llms/)
12. [**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/)
13. [**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/)
14. [**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/)
15. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
16. [**Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models arXiv:2307.14539**Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh*2023 · 81 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-jailbreak-pieces-compositional-adversarial-attacks/)
17. [**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/)
18. [**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/)
19. [**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/)
20. [**Safety Fine-Tuning at (Almost) No Cost: A Baseline for Vision Large Language Models arXiv:2402.02207**Yongshuo Zong, Ondrej Bohdal, Tingyang Yu, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/zong-2024-safety-fine-tuning-almost-no/)
21. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
22. [**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/)
23. **[Reasoning-to-Defend: Safety-Aware Reasoning Can Defend Large Language Models from Jailbreaking](https://md.research.elamur.ai/free/en/papers/zhu-2025-reasoning-defend-safety-aware-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junda Zhu, Lingyong Yan, Shuaiqiang Wang, et al.*2025 · 21 citations*
24. **[Jailbreak Large Vision-Language Models Through Multi-Modal Linkage](https://md.research.elamur.ai/free/en/papers/wang-2025-jailbreak-large-vision-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Wang, Xiaofei Zhou, Yichen Wang, et al.*2025 · 20 citations*
25. **[Refuse Whenever You Feel Unsafe: Improving Safety in LLMs via Decoupled Refusal Training](https://md.research.elamur.ai/free/en/papers/yuan-2025-refuse-whenever-you-feel-unsafe/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Youliang Yuan, Wenxiang Jiao, Wenxuan Wang, et al.*2025 · 19 citations*
26. **[HiddenDetect: Detecting Jailbreak Attacks against Multimodal Large Language Models via Monitoring Hidden States](https://md.research.elamur.ai/free/en/papers/jiang-2025-hiddendetect-detecting-jailbreak-attacks-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilei Jiang, Xinyan Gao, Tianshuo Peng, et al.*2025 · 15 citations*
27. [**Distilling LLM Agent into Small Models with Retrieval and Code Tools arXiv:2505.17612**Minki Kang, Jongwon Jeong, Seanie Lee, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kang-2025-distilling-llm-agent-small-models/)
28. **[Layer-Aware Representation Filtering: Purifying Finetuning Data to Preserve LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/li-2025-layer-aware-representation-filtering-purifying/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Li, Lijun Li, Zhenghao Lu, et al.*2025 · 11 citations*
29. **[Backdoors in RLVR: Jailbreak Backdoors in LLMs From Verifiable Reward](https://md.research.elamur.ai/free/en/papers/guo-2026-backdoors-rlvr-jailbreak-backdoors-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weiyang Guo, Zesheng Shi, Zeen Zhu, et al.*2026 · 10 citations*
30. **[Rethinking Jailbreak Detection of Large Vision Language Models with Representational Contrastive Scoring](https://md.research.elamur.ai/free/en/papers/hua-2026-rethinking-jailbreak-detection-large-vision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Peichun Hua, Hao Li, Shanghao Shi, et al.*2026 · 10 citations*
31. **[SafeKey: Amplifying Aha-Moment Insights for Safety Reasoning](https://md.research.elamur.ai/free/en/papers/zhou-2025-safekey-amplifying-aha-moment-insights/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kaiwen Zhou, Xuandong Zhao, Jayanth Srinivasa, et al.*2025 · 9 citations*
32. **[VisCRA: A Visual Chain Reasoning Attack for Jailbreaking Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/sima-2025-viscra-visual-chain-reasoning-attack/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bingrui Sima, Linhua Cong, Wenxuan Wang, et al.*2025 · 9 citations*
33. **[GAMBIT: A Gamified Jailbreak Framework for Multimodal Large Language Models](https://md.research.elamur.ai/free/en/papers/hu-2026-gambit-gamified-jailbreak-framework-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiangdong Hu, Yangyang Jiang, Qin Hu, et al.*2026 · 6 citations*
34. **[Visual Contextual Attack: Jailbreaking MLLMs with Image-Driven Context Injection](https://md.research.elamur.ai/free/en/papers/ziqi-2025-visual-contextual-attack-jailbreaking-mllms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miao Ziqi, Yi Ding, Lijun Li, et al.*2025 · 6 citations*
35. **[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*
36. **[SDD: Self-Degraded Defense against Malicious Fine-tuning](https://md.research.elamur.ai/free/en/papers/chen-2025-sdd-self-degraded-defense-against/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**ZiXuan Chen, Weikai Lu, Xin Lin, et al.*2025 · 4 citations*
37. **[CTRAP: Embedding Collapse Trap to Safeguard Large Language Models from Harmful Fine-Tuning](https://md.research.elamur.ai/free/en/papers/yi-2026-ctrap-embedding-collapse-trap-safeguard/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Biao Yi, Tiansheng Huang, Baolei Zhang, et al.*2026 · 3 citations*
38. **[SafeMT: Multi-turn Safety for Multimodal Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2026-safemt-multi-turn-safety-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Han Zhu, Juntao Dai, Jiaming Ji, et al.*2026 · 3 citations*
39. **[Universal Jailbreak Suffixes Are Strong Attention Hijackers](https://md.research.elamur.ai/free/en/papers/tov-2026-universal-jailbreak-suffixes-are-strong/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Matan Ben-Tov, Mor Geva, Mahmood Sharif*2026 · 3 citations*
40. **[Activation-Guided Local Editing for Jailbreaking Attacks](https://md.research.elamur.ai/free/en/papers/wang-2026-activation-guided-local-editing-jailbreaking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiecong Wang, Haoran Li, Hao Peng, et al.*2026 · 1 citation*
41. **[Beyond Surface-Level Detection: Towards Cognitive-Driven Defense Against Jailbreak Attacks via Meta-Operations Reasoning](https://md.research.elamur.ai/free/en/papers/pu-2026-beyond-surface-level-detection-cognitive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rui Pu, Chaozhuo Li, Rui Ha, et al.*2026 · 1 citation*
42. **[Enhancing the Safety of Medical Vision-Language Models by Synthetic Demonstrations](https://md.research.elamur.ai/free/en/papers/xue-2026-enhancing-safety-medical-vision-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhiyu Xue, Reza Abbasi-Asl, Ramtin Pedarsani*2026 · 1 citation*
43. **[Reasoning Up the Instruction Ladder for Controllable Language Models](https://md.research.elamur.ai/free/en/papers/zheng-2026-reasoning-up-instruction-ladder-controllable/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zishuo Zheng, Vidhisha Balachandran, Chan Young Park, et al.*2026 · 1 citation*
44. **[“Penny Wise, Pixel Foolish”: Bypassing Price Constraints in Multimodal Agents via Visual Adversarial Perturbations](https://md.research.elamur.ai/free/en/papers/qian-2026-penny-wise-pixel-foolish-bypassing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiachen Qian, Zhaolu Kang*2026 · 1 citation*
45. [**Can Small-Scale Data Poisoning Exacerbate Dialect-Linked Biases in Large Language Models? arXiv:2507.19195**Chaymaa Abbas, Mariette Awad, Razane Tajeddine*2025 · 1 citation*](https://md.research.elamur.ai/free/en/papers/abbas-2025-small-scale-data-poisoning-exacerbate/)
46. [**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/)
47. **[CrossGuard: Safeguarding MLLMs against Joint-Modal Implicit Malicious Attacks](https://md.research.elamur.ai/free/en/papers/zhang-2026-crossguard-safeguarding-mllms-against-joint/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xu Zhang, Hao Li, Zhichao Lu*2026*
48. **[Deactivating Refusal Triggers: Understanding and Mitigating Overrefusal in Safety Alignment](https://md.research.elamur.ai/free/en/papers/xue-2026-deactivating-refusal-triggers-understanding-mitigating/) [Workshop on Trustworthy NLP](https://md.research.elamur.ai/free/en/venues/trustnlp/)**Zhiyu Xue, Zimo Qi, Guangliang Liu, et al.*2026*
49. **[DMN: A Compositional Framework for Jailbreaking Multimodal LLMs with Multi-Image Inputs](https://md.research.elamur.ai/free/en/papers/xu-2026-dmn-compositional-framework-jailbreaking-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenzhuo Xu, Zhipeng Wei, Zonghao Ying, et al.*2026*
50. **[ECHA: Jailbreaking LVLMs via the Mismatch between Implicit Semantic Reconstruction and Explicit Safety Alignment](https://md.research.elamur.ai/free/en/papers/xu-2026-echa-jailbreaking-lvlms-mismatch-between/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chenxing Xu, Junyong Jiang, Zehu Zhang, et al.*2026*
51. **[From Narrow Unlearning to Emergent Misalignment in LLMs](https://md.research.elamur.ai/free/en/papers/mushtaq-2026-narrow-unlearning-emergent-misalignment-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna, et al.*2026*
52. **[Hard to Read, Easy to Jailbreak: How Visual Degradation Bypasses MLLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/song-2026-hard-read-easy-jailbreak-how/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhixue Song, Boyan Han, Yiwei Wang, et al.*2026*
53. **[How Do LLMs and VLMs Understand Viewpoint Rotation Without Vision? An Interpretability Study](https://md.research.elamur.ai/free/en/papers/yang-2026-how-do-llms-vlms-understand/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhen Yang, Ping Jian, Zhongbin Guo, et al.*2026*
54. **[Leave My Images Alone: Preventing Multi-Modal Large Language Models from Analyzing Images via Visual Prompt Injection](https://md.research.elamur.ai/free/en/papers/shao-2026-leave-my-images-alone-preventing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zedian Shao, Hongbin Liu, Yuepeng Hu, et al.*2026*
55. **[Let's Put Ourselves in Sally's Shoes: Shoes-of-Others Prefilling Improves Theory of Mind in Large Language Models](https://md.research.elamur.ai/free/en/papers/shinoda-2026-let-s-put-ourselves-sally/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kazutoshi Shinoda, Nobukatsu Hojo, Kyosuke Nishida, et al.*2026*
56. **[MLingualFC: Evaluating Jailbreak Vulnerabilities in Multilingual Vision-Language Models](https://md.research.elamur.ai/free/en/papers/makwana-2026-mlingualfc-evaluating-jailbreak-vulnerabilities-multilingual/) [Workshop on Multilinguality in the Era of Large Language Models](https://md.research.elamur.ai/free/en/venues/mellm/)**Rishabh Makwana, Mamta Mamta, Deeksha Varshney, et al.*2026*
57. **[More Thinking, Less Talking: Internalizing Deliberative Safety into LLM Parameters](https://md.research.elamur.ai/free/en/papers/wang-2026-more-thinking-less-talking-internalizing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guan Wang, Xuehai Tang, Biyu Zhou, et al.*2026*
58. **[OASIS: Mitigating Harmful Fine-tuning Attacks on LLMs via Orthogonal and Adaptive Safety Alignment Strategy](https://md.research.elamur.ai/free/en/papers/tang-2026-oasis-mitigating-harmful-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiayu Tang, Guowei Peng, Qiuhao Xie, et al.*2026*
59. **[Pruning Unsafe Tickets: A Resource-Efficient Framework for Safer and More Robust LLMs](https://md.research.elamur.ai/free/en/papers/si-2026-pruning-unsafe-tickets-resource-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wai Man Si, Mingjie Li, Michael Backes, et al.*2026*
60. **[Rejection-to-Acceptance Transition: Model Editing-Based Jailbreak Backdoor Injection Not Limited to Few Output Tokens](https://md.research.elamur.ai/free/en/papers/yang-2026-rejection-acceptance-transition-model-editing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiji Yang, Min Cai, Hao Xiong, et al.*2026*
61. **[Resolving the Security-Auditability Dilemma with Auditable Latent Chain-of-Thought Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-resolving-security-auditability-dilemma-auditable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guan Wang, Biyu Zhou, Xuehai Tang, et al.*2026*
62. **[Retrieval-Augmented Defense: Adaptive and Controllable Jailbreak Prevention for Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2026-retrieval-augmented-defense-adaptive-controllable/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guangyu Yang, Jinghong Chen, Jingbiao Mei, et al.*2026*
63. **[Revisiting Self-Play Preference Optimization: On the Role of Prompt Difficulty](https://md.research.elamur.ai/free/en/papers/xiao-2026-revisiting-self-play-preference-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yao Xiao, Jung-jae Kim, Roy Ka-Wei Lee, et al.*2026*
64. **[Safeguarding LLM Fine-tuning via Push-Pull Distributional Alignment](https://md.research.elamur.ai/free/en/papers/wang-2026-safeguarding-llm-fine-tuning-push/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haozhong Wang, Zhuo Li, Yibo Yang, et al.*2026*
65. **[StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt Generation](https://md.research.elamur.ai/free/en/papers/zheng-2026-stealthgraph-exposing-domain-specific-risks/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Huawei Zheng, Xinqi Jiang, Sen Yang, et al.*2026*
66. **[StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMs](https://md.research.elamur.ai/free/en/papers/luo-2026-structbreak-structural-cognitive-overload-induced/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Luo, Liu Xinran, TianTian Ji, et al.*2026*
67. **[The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-Training](https://md.research.elamur.ai/free/en/papers/zhang-2026-art-mis-alignment-how-fine/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Zhang, Hongwei Li, Yun Shen, et al.*2026*
68. **[Thinking Twice Makes Large Language Models Safer and More Helpful](https://md.research.elamur.ai/free/en/papers/mou-2026-thinking-twice-makes-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2026*
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