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cs.CL2026
AdaPlanBench: Evaluating Adaptive Planning in Large Language Model Agents under World and User Constraints
Jiayu Liu, Cheng Qian, Zhenhailong Wang +10
Planning for real-world problems by language models often involves both world and user constraints, which may not be fully specified upfront and are progressively disclosed through…
cs.CL2025
Context Engineering for Trustworthiness: Rescorla Wagner Steering Under Mixed and Inappropriate Contexts
Rushi Wang, Jiateng Liu, Cheng Qian +6
Incorporating external context can significantly enhance the response quality of Large Language Models (LLMs). However, real-world contexts often mix relevant information with disp…
cs.CL2025★ 1 cited
The Law of Knowledge Overshadowing: Towards Understanding, Predicting, and Preventing LLM Hallucination
Yuji Zhang, Sha Li, Cheng Qian +8
Hallucination is a persistent challenge in large language models (LLMs), where even with rigorous quality control, models often generate distorted facts. This paradox, in which err…