LongHorizon-Harness: Advancing Long-Horizon Agents for Real-World Tasks
Large language model (LLM) agents increasingly undertake long-horizon tasks that require sustained reasoning, tool use, and revision across many interdependent steps. However, existing agent harnesses maintain task execution, task state, and completion assessment within a growing context, making the state difficult to track and allowing incorrect self-assessments to propagate into later decisions. We reformulate long-horizon execution as a task-state management problem and propose LongHorizon-Ha
Record details
Published: 2 August 2026
Source: HuggingFace Daily Papers
Category: Research
Topics: Agents & autonomy
Retrieved: 5 August 2026
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How to cite this record
ethics.ai (2 August 2026), “LongHorizon-Harness: Advancing Long-Horizon Agents for Real-World Tasks,” evidence record 16238, https://ethics.ai/record/16238 (originally published by HuggingFace Daily Papers).
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