Proactive agents must decide whether, when, and how far to assist without an explicit request. Existing evaluations often rely on automated scores or binary verdicts, offering limited human diagnosis
HALO introduces a human-annotated benchmark and dataset to evaluate proactive agents, revealing that over-proactivity is the dominant failure mode.
Proactive agents must decide whether, when, and how far to assist without an explicit request. Existing evaluations often rely on automated scores or binary verdicts, offering limited human diagnosis of evidence use and intervention quality. To address these gaps, we introduce HALO, Human-Grounded GrAnular EvaLuation of PrOactive Agents. HALO-Arena covers 4 proactive need types, Dependency, Blockage, Risk, and Opportunity, across 10 everyday domains and 50 personal environments. Scenarios require agents to retrieve evidence from structured databases or unstructured documents before judging whether assistance is warranted and choosing its scope. On HALO-Arena, we construct HALO-8K, a…
Summary and abstract excerpt via Hugging Face Papers ↗ · arXiv.
HALO: Human-Grounded Granular Evaluation of Proactive Agents was first seen on Hugging Face · Daily papers on Nov 2, 2026. Since then it has appeared in 8 checks on 2 different days. Its best position was #25 of 30, reached on Nov 2, 23:28 UTC. It dropped off the list after Nov 3, 07:28 UTC.
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Not at the moment. It was last on the list on Nov 3, 07:28 UTC, after 2 days of trending.
#25 on Hugging Face · Daily papers, on Nov 2, 23:28 UTC. Trendoday checks this list every 120 minutes.
It was first seen on Nov 2, 2026 and has been on the list on 2 days (8 checks) since.