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arXiv AI By Egor Pakhomov, Erik Nijkamp

Parsing the Stream: A Live Trace Model for Long-Horizon Agents and Their Observers

Read the original on arXiv AI →

The paper introduces a live trace model that incrementally folds an append‑only event ledger into typed run state, producing per‑consumer views for both human observers and the agent itself. Evaluations show that for observers, the compiled view reduces input tokens by 14–15× and cost by 5–7× while improving accuracy from 0.48 to 0.85–0.87. For agents, maintaining running statistics in per‑step state enables success on 120‑link sequential tasks where full‑context prompting fails, and a prompt‑level scratchpad matches the fold’s accuracy at lower cost.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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