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PresenceBench: An Exploratory Evaluation of Large Language Model Adaptation to User State

Paper recorded by Signals 4 on 2026-10-16 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-16 on arXiv · recorded by Signals 4 on 2026-10-19

Category: cs.AI · 人工智能 · first seen 2026-10-19

Abstract

Presence-aware intelligence is the capacity of an AI system's intelligence layer to adapt appropriately to the functional state of the person it serves (here readiness, flow, and stability) while preserving task quality and safety. We introduce PresenceBench, an instrument for measuring it. PresenceBench evaluates how the intelligence layer uses a supplied state, not how that state is sensed, and

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#274 most recent of 960 cs.AI papers we have recorded · ↑ newer: TUPLE-Bench: Evaluating and Mitigating Privacy-Utility Trade-offs in T · ↓ older: GEMS: Molecular Structure Elucidation as Learned Search over Isomer Gr
Cite this page: PresenceBench: An Exploratory Evaluation of Large Language Model Adaptation to User State: the #274 most recent of 960 cs.AI papers we have recorded (as of 2026-10-16). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/presencebench-an-exploratory-evaluation-of-large-language-model-adaptation-to-us.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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