MemReread: Enhancing Agentic Long-Context Reasoning via Memory-Guided Rereading

MemReread is a new agentic long‑context reasoning method that uses memory‑guided rereading instead of intermediate retrieval. By decomposing questions and selectively rereading when the final memory is insufficient, it recovers indirect evidence that might otherwise be lost during memory overwriting. A reinforcement‑learning framework further improves length extrapolation and adaptively controls the number of rereading passes, allowing MemReread‑4B to outperform strong baselines on long‑context tasks while keeping linear time complexity.

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• agents
• reinforcement-learning