---
title: "Who cites Xiao Ma — 93 papers of our library — Elamur Research"
description: "93 papers of the Elamur Research library cite the works of Xiao Ma, found in their bibliographies; the most cited first."
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# Who cites Xiao Ma

93 citations of their works from 93 papers of our library (of the 149,439 whose bibliographies we read) · 35 with a page here, the most cited first · [← Xiao Ma](https://md.research.elamur.ai/free/en/authors/xiao-ma/)

1. [**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/)
2. **[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*
3. **[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*
4. **[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*
5. [**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/)
6. **[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*
7. **[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*
8. **[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*
9. **[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*
10. **[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*
11. **[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*
12. **[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*
13. **[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*
14. **[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*
15. **[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*
16. **[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*
17. [**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/)
18. [**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/)
19. **[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*
20. **[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*
21. **[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*
22. **[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*
23. **[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*
24. **[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*
25. **[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*
26. **[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*
27. **[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*
28. **[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*
29. **[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*
30. **[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*
31. **[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*
32. **[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*
33. **[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*
34. **[TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment](https://md.research.elamur.ai/free/en/papers/tan-2026-triplay-rl-tri-role-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhewen Tan, Wenhan Yu, Jianfeng Si, et al.*2026*
35. **[When Safety Alignment Fails to Generalize: Probing with Language Game Jailbreaks](https://md.research.elamur.ai/free/en/papers/long-2026-when-safety-alignment-fails-generalize/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zewen Long, Yu Peng, Fangming Dong, et al.*2026*

58 more citing papers of our library have no page here yet.

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