Meng Han
Meng Han has 4 papers in our library, in 2025–2026, most of them on Language models & pretraining; often with Zhenhua Xu, Changting Lin, Wenpeng Xing.
OpenAlex · ORCID · Wikidata · h-index 1 · 10 works · 1 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 16 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9173
Affiliations
Fields, topics and concepts
📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Computer Science · 4 worksArtificial Intelligence · 4 worksComputer Vision and Pattern Recognition · 2 worksHardware and Architecture · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 worksLiterature and Literary Theory · 1 work
🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 2 works
Works by year
2020s
Papers
- MEraser: An Effective Fingerprint Erasure Approach for Large Language Models (2025 · 11 citations)
Backdoor-based fingerprinting lets LLM owners prove ownership through secret trigger–response pairs, but little work has tested how easily these marks can be removed. - CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation Backdoor (2025 · 4 citations)
The paper tackles ownership verification for large language models that may be stolen and redistributed. Earlier fingerprinting approaches each have a weak spot. Rare-token triggers stand out under perplexity checks. Natural-looking triggers such as HashChain tend to vanish after fine-tuning or merging. Most… - AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-Playing (2026 · 2 citations)
LLM role-playing systems often feel flat. They mostly generate dialogue, treat the surroundings as static backdrop, and assume one fixed scene with a fixed cast. AdaMARP tackles both problems. Each turn interleaves four marked elements: [Thought], (Action), <Environment> and plain Speech, so world states and events… - MCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AI (2026 · 1 citation)
Connecting LLM agents to external tools through the Model Context Protocol (MCP) opens new attack routes, including prompt injection, Tool Poisoning, Shadowing and data exfiltration.
All works
- MEraser: An Effective Fingerprint Erasure Approach for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jingxuan Zhang, Zhenhua Xu, Rui Hu, et al.2025 · 11 citations
- CTCC: A Robust and Stealthy Fingerprinting Framework for Large Language Models via Cross-Turn Contextual Correlation BackdoorConference on Empirical Methods in Natural Language Processing (EMNLP)Zhenhua Xu, Xixiang Zhao, Xubin Yue, et al.2025 · 4 citations
- AdaMARP: An Adaptive Multi-Agent Interaction Framework for General Immersive Role-PlayingFindings of the Association for Computational LinguisticsZhenhua Xu, Dongsheng Chen, Shuo Wang, et al.2026 · 2 citations
- MCP-Guard: A Multi-Stage Defense-in-Depth Framework for Securing Model Context Protocol in Agentic AIFindings of the Association for Computational LinguisticsWenpeng Xing, Zhonghao Qi, Yupeng Qin, et al.2026 · 1 citation
- Silencing the Guardrails: Inference-Time Jailbreaking via Dynamic Contextual Representation Ablation ↗Findings of the Association for Computational Linguistics: ACL 2026 · no summary yetWenpeng Xing et al.2026
Co-authors here
Venues
- Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2025
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
- Findings of the Association for Computational Linguistics: ACL 2026
Cited by
Updated
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