acceptodds
Published as a conference paper at NeurIPS 2026

Git Context Controller: Manage the Context of Agents by Agentic Git

Junde Wu, Minhao Hu, Jiayuan Zhu, Shengda Zhu, Jiazhen Pan, Fenglin Liu, Yuyuan Liu, Min Xu, Yueming Jin

Abstract

Large language model (LLM) agents have demonstrated strong capabilities in long-horizon tasks by interleaving reasoning with tool use. However, as these agents scale to complex workflows such as software engineering and open-ended research, context management becomes a fundamental bottleneck: interaction histories grow unbounded, become costly to maintain, and are difficult to reuse across sessions and agents. We introduce Git-Context-Controller (GCC), a structured context management framework inspired by software version control systems. GCC elevates agent context from a transient token stream to a persistent, navigable memory workspace with explicit operations—COMMIT, BRANCH, MERGE, and CONTEXT, that enable milestone-based checkpointing, isolated exploration of alternative reasoning paths, and hierarchical retrieval of historical context. By organizing agent memory as a versioned file system, GCC allows agents to manage long-term goals, recover and transfer reasoning across sessions, and coordinate multi-trajectory problem solving in a principled manner. Empirically, agents equipped with GCC achieve state-of-the-art performance on both SWE-Bench and BrowseComp benchmarks. On SWE-Bench Verified, GCC improves task resolution by over 13% relative to strong long-context baselines and outperforms 26 existing open and commercial systems, reaching over 80% success rate. The project will be open-sourced for the research community.

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