Large language model (LLM) based multi-agent systems often rely on predefined collaboration structures, limiting their adaptability to evolving task requirements. Although recent approaches enable dynamic orchestration, trajectory-level rewards they apply assign one outcome to each decision, ofen struggling to identify...
Yi-Rou Ge, Pan Wang, Xue-Hao Cui et al.· 0 citations
CUA-Recovery is introduced, a benchmark comprising test and training suites across multiple desktop applications using ReRail, a framework for synthesizing long-horizon tasks and trajectories in a persistent desktop environment that shows that agents struggle both to recognize inherited errors and to complete the task.
Xue Hu, Hao-Ming Li, Yuxuan Wang et al.· 0 citations
SAFE-Mem is a fine-grained memory governance framework that improves security while preserving legitimate memory use and attains the lowest attack success among defenses that retain legitimate memory, at least 77% below the strongest of them, and the highest answer accuracy of all evaluated defenses.
Hao-Ming Li, Ding-Yi Kang, Xue Hu et al.· 0 citations
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