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Learning When Human Decisions Matter: Executor-Relative Consultation Value for LLM Agents
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers introduced a framework to optimize when LLM agents consult humans under strict human attention budget constraints.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 5 November 2026
- Collected by OneBench
- 6 Nov 2026, 02:01 UK
Stored source excerpt
arXiv:2611.05814v1 Announce Type: new Abstract: Large language models increasingly automate complex tasks, but human decision capacity does not scale with their capabilities. In many applications,…
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