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Knowing When to Intervene: Causal Evaluation of AI Agents
arXiv cs.LG — Machine Learning
Factual evidence
What the source reports
Researchers propose a causal evaluation framework to decide when human intervention or secondary verification is needed for runtime AI agents.
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- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.LG — Machine Learning · RESEARCH
- Published by source
- 11 November 2026
- Collected by OneBench
- 12 Nov 2026, 02:02 UK
- Original headline
- Knowing When to Intervene: Causal Evaluation of AI Agents ↗
Stored source excerpt
arXiv:2611.09792v2 Announce Type: replace-cross Abstract: Current evaluations of agentic AI systems primarily rely on benchmarks. However, the static nature of benchmarks makes them uninformative about…
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