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ContextPilot: Teaching Agents for Proactive Context Management via Fine-grained RL

Paper recorded by Signals 4 on 2026-08-28 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-08-28 on arXiv · recorded by Signals 4 on 2026-08-31

Category: cs.CL · 自然语言处理 · first seen 2026-08-31

Abstract

Long-horizon agentic tasks require large language models (LLMs) to iteratively retrieve, integrate, and maintain dispersed information across multi-turn interactions, but preserving all interaction histories leads to a continuously growing working context. Recent proactive context management methods allow models to edit their own working context with specialized tools, yet they still face three ke

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#175 most recent of 186 cs.CL papers we have recorded · ↑ newer: Blind Men and the Elephant: Probing the Epistemic Myopia of LLMs under · ↓ older: Stranger, Fan, or Peer? A Systematic Study on the Role of Interlocutor
Cite this page: ContextPilot: Teaching Agents for Proactive Context Management via Fine-grained RL: the #175 most recent of 186 cs.CL papers we have recorded (as of 2026-08-28). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/contextpilot-teaching-agents-for-proactive-context-management-via-fine-grained-r.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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