Context Language Models
- Published
- Source
- arXiv
- Paper number
- 1139
- Field
- AI / General
- arXiv ID
- 2609.37725
Key points
- Context Language Models expose the live context as a file that the model can directly edit through general code tools.
- Edits are reflected in the next model call, and the approach extends to multi-agent systems that manage multiple context files.
- On BrowseComp-Plus with Qwen3.6-27B, accuracy is 11.4% higher in relative terms than the strongest baseline, with 21.5% fewer prefix-reuse FLOPs.
- Natural-language guidance and reinforcement learning can improve context-management strategies, while a separate suffix-cache reuse method reduces compute by 35% relative to standard SGLang in the reported evaluation.
- Editable context can become a new channel for persistent malicious instructions, requiring context-integrity protections alongside flexible management.
Paper links
External research summaries. These are not HDATF publications or measured product results.