Turning context into an editable file: CLM lets models manage their own context, raising BrowseComp-Plus accuracy by 11.4% with 21.5% fewer FLOPs
The work introduces Context Language Models (CLMs), which mirror a model's live context as a freely editable file that the model can rewrite with Bash, shifting context management from external harness control to an intrinsic model capability; applied zero-shot to existing models such as Qwen3.6-27B and GPT5.6-Sol, CLMs achieve 11.4% higher accuracy with 21.5% fewer prefix-reuse FLOPs than the strongest baseline on BrowseComp-Plus, 5% higher scores with 59% fewer FLOPs on 12-hour EdgeBench, and 65% greater end-to-end speedup at the same compute on a 24-hour multi-repository agent-swarm task, and can further learn context-management strategies through natural-language instructions, textual evolution, and online reinforcement learning.