AI RESEARCH
Contexts are Never Long Enough: Structured Reasoning for Scalable Question Answering over Long Document Sets
arXiv CS.AI
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ArXi:2604.22294v1 Announce Type: cross Real-world document question answering is challenging. Analysts must synthesize evidence across multiple documents and different parts of each document. However, any fixed LLM context window can be exceeded as document collections grow. A common workaround is to decompose documents into chunks and assemble answers from chunk-level outputs, but this