Researchers introduced PARSER, a method that decouples document traversal from reasoning depth to address the sensitivity to evidence placement and linear inference latency that affect sequential memory agents on long documents. Sequential memory agents read chunks one at a time while maintaining a compact memory state, which ties inference latency linearly to document length. PARSER is designed to read in parallel and reason in depth for long-context LLM agents.
Sequential memory agents process long documents by reading chunks one after another while maintaining a compact memory state, coupling document traversal to reasoning depth. This coupling introduces sensitivity to evidence placement and ties inference latency linearly to document length. We introduc
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