DocAtlas: Long-Document Understanding as Mutable-State Interaction
Long-document understanding requires models to find and combine evidence across many pages, layouts, tables, figures, and charts. Existing retrieval-augmented systems usually select evidence from a static index before generation, while recent agentic systems add multi-turn tool use but often rely on frozen proprietary backbones whose behavior is set by prompts. We present DocAtlas, a system that treats long-document understanding as a mutable-state information-seeking process. We instantiate DocAtlas as a mutable document harness: an external environment that determines what document information is searched, read, stored, reviewed, and shown to the model at each step. Given a document and...
| Authors | Hongchen Wei, Yuanzhe Wang, Bei Liu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 21 July 2026 |
| Last updated at source | 21 July 2026 |
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