Author

Chao Ning

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#artificial intelligence Preprint Sep 2026

When Can Agents Forget Their Reasoning? ICLR for Long-Horizon Agent Context Compression

Long horizon language model agents continually accumulate reasoning history, increasing context length and inference cost even after earlier decisions have been executed and observed. Unlike static Chain of Thought compression, removing historical reasoning can change future actions and the resulting interaction trajec...

Ming-Xuan Wang, Fei Luo, Bo Wang et al. · 0 citations

#small language model Preprint Sep 2026

DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

Direct Relational Set-Risk Pruning is introduced, which formulates agent-history compression as risk-constrained selection over deletion sets and shows that decision-conditioned relations, retained-context information, pair interactions, and abstention each contribute to reliable pruning.

Ming-Xuan Wang, Bo Wang, Fei Luo et al. · 0 citations