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    Reviewed current signal · 2026-04-20

    HiL-Bench: does an agent know when to ask for help?

    Reviewed through September 18, 2026

    2026-04-20 · Reviewed current signal

    HiL-Bench: does an agent know when to ask for help?

    Era
    Current reviewed signal
    Theme
    Agent reliability & evaluation
    Evidence form
    Benchmark
    Source of record
    Scale Labs
    Source tier
    A
    Impact
    High
    School / paradigm
    Not recorded — current signals carry no formal school
    Application
    Enterprise, coding, and data agents
    Researchers
    Not recorded

    Understand

    Plain-language record, transferred from the reviewed source module.

    What changed. Scale reports that agents solved up to 89% of complex tasks with complete information, but performance fell as low as 4% after key details were removed; agents often guessed instead of escalating.

    Technique / discovery. Controlled underspecification, ambiguity injection, clarification scoring, and human-in-the-loop evaluation.

    Apply

    Professional implication, only where the reviewed record states one.

    Why it matters. Selective escalation and calibrated clarification are core production capabilities, not UX niceties.

    Application. Enterprise, coding, and data agents

    Verify

    Evidence status, stated limitations, and the external sources this record actually carries.

    Evidence maturity. Benchmark (source tier A)

    Identified bottleneck. Agents do not reliably detect missing or contradictory requirements.

    Caveat / evidence note. Benchmark construction and reported results are first party; real organizations have different escalation costs.

    Review status. Reviewed. User requested: Yes.

    Reproduce

    A reproduction tutorial is linked only when one exists for this exact record.

    A reproduction tutorial is not yet available for this entry. The closest reviewed material is Reliability, uncertainty, and evaluation and Human–AI interaction and adoption.

    Cite or share

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