AgentHorizon: Evaluating Agentic Judges for Long-Horizon Computer-Use Tasks
Factual evidence
What the source reports
Researchers introduced AgentHorizon to evaluate automated LLM judges assessing computer-use agents on complex multi-step tasks.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 9 October 2026
- Collected by OneBench
- 10 Oct 2026, 03:02 UK
Stored source excerpt
arXiv:2610.11050v1 Announce Type: cross Abstract: Computer-use agents are capable of completing complex tasks, increasing the use of automatic judges to determine success, either for training…
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The factual summary is a OneBench synthesis, not a quotation or independent verification. Collection time is not publication time. Open the source for its full context; related reporting can share the same underlying announcement.
OneBench interpretation
Institutional assessment
So what
Automated evaluation of complex multi-application desktop agents remains unreliable, complicating governance and validation for automated workflows.
Do what
Monitor research into automated evaluation frameworks for computer-use agents before relying on LLM judges in production controls.