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cs.AI2026
ComplexMCP: Evaluation of LLM Agents in Dynamic, Interdependent, and Large-Scale Tool Sandbox
Yuanyang Li, Xue Yang, Longyue Wang +2
Current LLM agents are proficient at calling isolated APIs but struggle with the "last mile" of commercial software automation. In real-world scenarios, tools are not independent;…
cs.CL2026
DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models
Shaokai He, Kaiwen Wei, Xinyi Zeng +5
The "reversal curse" refers to the phenomenon where large language models (LLMs) exhibit predominantly unidirectional behavior when processing logically bidirectional relationships…
cs.CR2026
Safe-FedLLM: Delving into the Safety of Federated Large Language Models
Mingxiang Tao, Yu Tian, Wenxuan Tu +3
Federated learning (FL) addresses privacy and data-silo issues in the training of large language models (LLMs). Most prior work focuses on improving the efficiency of federated lea…