Coding Agents are Effective Long-Context Processors
Large Language Models (LLMs) have demonstrated remarkable progress in scaling to access massive contexts. However, the access is via the latent and uninterpretable attention mechanisms, and LLMs fail to effective process long context, exhibiting significant performance degradation as context length increases. In this work, we study whether long-context processing can be externalized from latent attention into explicit, executable interactions, by allowing coding agents to organize text in file systems and manipulate it using its native tools. We evaluate off-the-shelf frontier coding agents as the general interface for tasks that require processing long contexts, including long-context re...
| Authors | Weili Cao, Xunjian Yin, Bhuwan Dhingra et al. |
|---|---|
| Primary category | cs.CL |
| Published | 20 March 2026 |
| Last updated at source | 20 March 2026 |
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