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Who cites Xiangyu Qi

905 citations of their works from 772 papers of our library (of the 149,439 whose bibliographies we read) · 215 with a page here, the most cited first · page 3 of 3 · 201–215 · ← Xiangyu Qi

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  1. SEAD: A Surrogate-free Label-only Membership Inference Attack against Pre-trained LLMs with Semantic-Aware DensityFindings of the Association for Computational LinguisticsBiao Yi, Jiahao Li, Yiming Li, et al.2026
  2. Seeing the Other Side: Diagnostic Tasks for Viewpoint Reasoning in Vision–Language ModelsLanguage Resources and Evaluation Conference (LREC)Makoto Takenaka, Hitomi Yanaka2026
  3. SGT: Securing Open-Source LLMs Against Malicious Fine-tuning via Safety Guidance TriggerAnnual Meeting of the Association for Computational Linguistics (ACL)Sunguk Shin, Fangzhao Wu, Byung-Jun Lee, et al.2026
  4. SLIM: Stealthy Low-Coverage Black-Box Watermarking via Latent-Space Confusion ZonesFindings of the Association for Computational LinguisticsHengyu WU, Yang Cao2026
  5. StealthGraph: Exposing Domain-Specific Risks in LLMs through Knowledge-Graph-Guided Harmful Prompt GenerationAnnual Meeting of the Association for Computational Linguistics (ACL)Huawei Zheng, Xinqi Jiang, Sen Yang, et al.2026
  6. StructBreak: Structural Cognitive Overload-Induced Safety Failures in MLLMsFindings of the Association for Computational LinguisticsYang Luo, Liu Xinran, TianTian Ji, et al.2026
  7. Synthetic Eggs in Many Baskets: The Impact of Synthetic Data Diversity on LLM Fine-TuningFindings of the Association for Computational LinguisticsMax Schaffelder, Albert Gatt2026
  8. Teach a Reward Model to Correct Itself: Reward Guided Adversarial Failure Discovery for Robust Reward ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Pankayaraj Pathmanathan, Furong Huang2026
  9. The Art of (Mis)alignment: How Fine-Tuning Methods Effectively Misalign and Realign LLMs in Post-TrainingFindings of the Association for Computational LinguisticsRui Zhang, Hongwei Li, Yun Shen, et al.2026
  10. Thinking Twice Makes Large Language Models Safer and More HelpfulFindings of the Association for Computational LinguisticsYutao Mou, Yuxiao Luo, Shikun Zhang, et al.2026
  11. TrajGuard: Streaming Hidden-state Trajectory Detection for Decoding-time Jailbreak DefenseFindings of the Association for Computational LinguisticsCheng Liu, Xiaolei Liu, Xingyu Li, et al.2026
  12. TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety AlignmentAnnual Meeting of the Association for Computational Linguistics (ACL)Zhewen Tan, Wenhan Yu, Jianfeng Si, et al.2026
  13. Visual Self-Fulfilling Alignment: Shaping Safety-Oriented Personas via Threat-Related ImagesAnnual Meeting of the Association for Computational Linguistics (ACL)Qishun Yang, Shu Yang, Lijie Hu, et al.2026
  14. When Safety Alignment Fails to Generalize: Probing with Language Game JailbreaksFindings of the Association for Computational LinguisticsZewen Long, Yu Peng, Fangming Dong, et al.2026
  15. When Similar Means Different: Evaluating LLMs on Arabic–Hebrew CognatesJunhong Liang, Noor Abo Mokh, Bashar Alhafni2026

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