Author

Bo Wang

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#artificial intelligence Preprint Sep 2026

StateComp: Learning When to Compress History in Long Horizon Agents

Long-horizon agents continuously accumulate interaction history during task execution, yet the importance of past interactions changes as the agent state evolves. Existing context management methods largely compress history based on fixed windows, periodic schedules, or current relevance, overlooking a more fundamental...

Ming-Xuan Wang, Hong-Yue Chen, Ying-Long Guo et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Memory Control Signals Emerge Before Action in Long Horizon Agents

Long horizon language model agents continuously accumulate interaction history, increasing computational cost while making relevant information harder to preserve and reuse. Existing context management methods mainly focus on how to compress or retrieve history, but largely leave open whether the model itself already r...

Ming-Xuan Wang, Guo-Run Yao, Fei Luo et al. · 0 citations