LongHorizon-Harness targets long-horizon agent state
The research harness separates task state from execution and verifies updates through an audit loop.
Why it matters
The work addresses a core failure mode in long-running agents: compounding errors from stale or incorrect self-assessments. Explicit, independently verified state management could make agent systems more reliable across tool-heavy workflows.
The key points
- 1.LongHorizon-Harness stores task state outside the execution context.
- 2.The MEA loop verifies updates before the next subtask.
- 3.Reported benchmark gains include Qwen 3.7-Plus on WeaveBench.
Researchers proposed LongHorizon-Harness, a framework for long-horizon LLM agents that manages task state outside the model’s growing context. Its Manage-Execute-Audit loop uses a manager to choose subtasks, a fresh-context executor to act, and a read-only auditor to verify environment state before updating the task record. The paper reports gains for Qwen 3.7-Plus on WeaveBench, Terminal-Bench 2.1 and OSWorld 2.0.
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When building long-horizon agents, separate task state from execution context and verify state changes against the environment before continuing.
Sources & original reporting
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