mlsanityData to 14 Oct 2026

Git Context Controller: Manage the Context of LLM-based Agents like Git

arXiv 2508.00031 ↗First posted 30 Jul 2025cs.SEcited by 15

On the map: LLM agents and tool use → Agent memory systems

Abstract (arXiv)

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 -- textttCOMMIT, textttBRANCH, textttMERGE, and textttCONTEXT, 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. https://github.com/ImprintLab/git-context-controller

Key facts. Cited by 15 papers in the map (data through 14 Oct 2026). Placed in Agent memory systems, one of 16 directions in LLM agents and tool use. Builds on 9 of its 33 references that are in the map. First posted on arXiv 30 Jul 2025.

Builds on

9 of 33 references.

References · 9

  1. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  2. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  3. 2024SWE-agent: Agent-Computer Interfaces Enable Automated Software Engineeringcited by 1,737
  4. 2024Agentless: Demystifying LLM-based Software Engineering Agentscited by 421
  5. 2025MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agentcited by 246
  6. 2025Agentic Reasoning: A Streamlined Framework for Enhancing LLM Reasoning with Agentic Toolscited by 106
  7. 2024CodeR: Issue Resolving with Multi-Agent and Task Graphscited by 91
  8. 2024MarsCode Agent: AI-native Automated Bug Fixingcited by 71
  9. 2024MASAI: Modular Architecture for Software-engineering AI Agentscited by 49

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 15.

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  1. 2026Git-Assistant: Planning-Based Support for Updating Git Repositories
  2. 2026GitOfThoughts: Version-Controlled Reasoning and Agent Memory You Can Replay, Diff, and Merge
  3. 2026Why Git Is the Memory Solution for the Agentic Development Lifecycle
  4. 2025Context as a Tool: Context Management for Long-Horizon SWE-Agents
  5. 2026Context as an Environment: Programmatic Context Management for Long-Horizon Agents
  6. 2025AgentGit: A Version Control Framework for Reliable and Scalable LLM-Powered Multi-Agent Systems
  7. 2026Self-GC: Self-Governing Context for Long-Horizon LLM Agents
  8. 2026ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents