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Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval , pages=

Not all relevance scores are equal: Efficient uncertainty, calibration modeling for deep retrieval models , author=

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Can LLMs Take Retrieved Information with a Grain of Salt?

cs.CL · 2026-05-07 · unverdicted · novelty 5.0

LLMs exhibit systematic failures in obeying expressed certainty in retrieved contexts, but a combination of prior reminders, certainty recalibration, and context simplification reduces obedience errors by 25%.

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  • Can LLMs Take Retrieved Information with a Grain of Salt? cs.CL · 2026-05-07 · unverdicted · none · ref 27

    LLMs exhibit systematic failures in obeying expressed certainty in retrieved contexts, but a combination of prior reminders, certainty recalibration, and context simplification reduces obedience errors by 25%.