Author

Xiaoxiao Li

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Preprint Aug 2026

MESA:Task-Adaptive Multi-Structure Evidence Selection for Long-Horizon Agent Memory

This work proposes MESA (a Multi-structure Evidence Selection framework for long-horizon Agent), which builds five complementary structure views of each trajectory and learns from end-to-end answer-level feedback to select and fuse a query-specific subset for a frozen answer model.

Bei-Di Zhao, Yaoqi Chen, Yuru Feng et al. · 1 citation