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Zheyuan Liu

Do LLMs Catch Their Own Mistakes? A Comprehensive Benchmark for Reflective Tool Use LLMs
2026 · Zheyuan Liu, Liqiang Xiao, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
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Knowledge Control for Responsible Generative AI: Bridging Academia, Industry, and Society
2026 · Zheyuan Liu, Yixin Wan, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
2026 · Nobin Sarwar, Shubhashis Roy Dipta, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
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MTMCS-Bench: Evaluating Contextual Safety of Multimodal Large Language Models in Multi-Turn Dialogues
2026 · Zheyuan Liu, Dongwhi Kim, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
Addressing Overthinking in Large Vision-Language Models via Gated Perception-Reasoning Optimization
2026 · Xingjian Diao, Zheyuan Liu, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
Behavior Knowledge Merge in Reinforced Agentic Models
2026 · Xiangchi Yuan, Dachuan Shi, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting
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AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning
2026 · Mengzhao Jia, Zhihan Zhang, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
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Works count: 7
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