---
title: "Who cites Xuhao Hu — 107 papers of our library"
description: "107 papers of the Elamur Research library cite the works of Xuhao Hu, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/xuhao-hu/cited-by/"
---
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# Who cites Xuhao Hu

114 citations of their works from 107 papers of our library (of the 149,439 whose bibliographies we read) · 31 with a page here, the most cited first · [← Xuhao Hu](https://md.research.elamur.ai/free/en/authors/xuhao-hu/)

1. **[WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://md.research.elamur.ai/free/en/papers/han-2024-wildguard-open-one-stop-moderation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Seungju Han, Kavel Rao, Allyson Ettinger, et al.*2024 · 165 citations*
2. [**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/)
3. **[AudioBench: A Universal Benchmark for Audio Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-audiobench-universal-benchmark-audio-large/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Xunlong Zou, Geyu Lin, et al.*2025 · 77 citations*
4. [**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/)
5. [**A Survey of Efficient Reasoning for Large Reasoning Models: Language, Multimodality, and Beyond arXiv:2503.21614**Xiaoye Qu, Yafu Li, Zhao-Chen Su, et al.*2025 · 55 citations*](https://md.research.elamur.ai/free/en/papers/qu-2025-survey-efficient-reasoning-large-reasoning/)
6. [**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/)
7. **[VLSBench: Unveiling Visual Leakage in Multimodal Safety](https://md.research.elamur.ai/free/en/papers/hu-2025-vlsbench-unveiling-visual-leakage-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuhao Hu, Dongrui Liu, Hao Li, et al.*2025 · 32 citations*
8. **[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*
9. **[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*
10. [**SaRO: Enhancing LLM Safety through Reasoning-based Alignment arXiv:2504.09420**Yutao Mou, Yuxiao Luo, Shikun Zhang, et al.*2025 · 11 citations*](https://md.research.elamur.ai/free/en/papers/mou-2025-saro-enhancing-llm-safety-through/)
11. **[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*
12. **[FanarGuard: A Culturally-Aware Moderation Filter for Arabic Language Models](https://md.research.elamur.ai/free/en/papers/fatehkia-2026-fanarguard-culturally-aware-moderation-filter/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Masoomali Fatehkia, Enes Altinisik, Husrev Taha Sencar*2026 · 5 citations*
13. **[LED-Merging: Mitigating Safety-Utility Conflicts in Model Merging with Location-Election-Disjoint](https://md.research.elamur.ai/free/en/papers/ma-2025-led-merging-mitigating-safety-utility/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qianli Ma, Dongrui Liu, Qian Chen, et al.*2025 · 5 citations*
14. [**Chinese SafetyQA: A Safety Short-form Factuality Benchmark for Large Language Models arXiv:2412.15265**Yingshui Tan, Boren Zheng, Baihui Zheng, et al.*2024 · 4 citations*](https://md.research.elamur.ai/free/en/papers/tan-2024-chinese-safetyqa-safety-short/)
15. **[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*
16. **[ToolSafe: Enhancing Tool Invocation Safety of LLM-based agents via Proactive Step-level Guardrail and Feedback](https://md.research.elamur.ai/free/en/papers/mou-2026-toolsafe-enhancing-tool-invocation-safety/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yutao Mou, Zhangchi Xue, Lijun Li, et al.*2026 · 3 citations*
17. **[SafeConstellations: Mitigating Over-Refusals in LLMs Through Task-Aware Representation Steering](https://md.research.elamur.ai/free/en/papers/maskey-2026-safeconstellations-mitigating-over-refusals-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Utsav Maskey, Sumit Yadav, Mark Dras, et al.*2026 · 1 citation*
18. **[USB: A COMPREHENSIVE AND UNIFIED SAFETY EVALUATION BENCHMARK FOR MULTIMODAL LARGE LANGUAGE MODELS](https://md.research.elamur.ai/free/en/papers/zheng-2026-usb-comprehensive-unified-safety-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Baolin Zheng, Guanlin Chen, Qingyang Teng, et al.*2026 · 1 citation*
19. **[When Helpers Become Hazards: A Benchmark for Analyzing Multimodal LLM-Powered Safety in Daily Life](https://md.research.elamur.ai/free/en/papers/lou-2026-when-helpers-become-hazards-benchmark/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinyue Lou, Xu Jinan, Jingyi Yin, et al.*2026 · 1 citation*
20. **[Adaptive Prompt Optimization for Open-Ended Tasks: Uncertainty Preference as a Secondary Signal](https://md.research.elamur.ai/free/en/papers/zhang-2026-adaptive-prompt-optimization-open-ended/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shuyang Zhang, Zhixuan Liu, Zhichen Dong, et al.*2026*
21. **[Are All Prompt Components Value-Neutral? Understanding the Heterogeneous Adversarial Robustness of Dissected Prompt in LLMs](https://md.research.elamur.ai/free/en/papers/zheng-2026-are-all-prompt-components-value/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yujia Zheng, Tianhao Li, Haotian Huang, et al.*2026*
22. **[CARO: Chain-of-Analogy Reasoning Optimization for Robust Content Moderation](https://md.research.elamur.ai/free/en/papers/wu-2026-caro-chain-analogy-reasoning-optimization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bingzhe Wu, Haotian Lu, Yuchen Mou*2026*
23. **[Jailbreaking Large Language Models with Morality Attacks](https://md.research.elamur.ai/free/en/papers/su-2026-jailbreaking-large-language-models-morality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ying Su, Zheng Mingen, Weili Diao, et al.*2026*
24. **[Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks](https://md.research.elamur.ai/free/en/papers/sarwar-2026-multimodal-unlearning-across-vision-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu, et al.*2026*
25. **[Safe-FedLLM: Delving into the Safety of Federated Large Language Models](https://md.research.elamur.ai/free/en/papers/tao-2026-safe-fedllm-delving-into-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mingxiang Tao, Yu Tian, Wenxuan Tu, et al.*2026*
26. **[Simple Role Assignment is Extraordinarily Effective for Safety Alignment](https://md.research.elamur.ai/free/en/papers/ziheng-2026-simple-role-assignment-is-extraordinarily/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhou Ziheng, Jiakun Ding, Zhaowei Zhang, et al.*2026*
27. **[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*
28. **[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*
29. **[Towards Understanding the Robustness of Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/saiyed-2026-understanding-robustness-sparse-autoencoders/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ahson Saiyed, Sabrina Sadiekh, Chirag Agarwal*2026*
30. **[Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related Images](https://md.research.elamur.ai/free/en/papers/yang-2026-visual-self-fulfilling-alignment-shaping/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qishun Yang, Shu Yang, Lijie Hu, et al.*2026*
31. **[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*

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

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