Who Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust Calibration
Paper recorded by Signals 4 on 2026-10-22 in cs.AI. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-22 on arXiv · recorded by Signals 4 on 2026-10-23
Category: cs.AI · 人工智能 · first seen 2026-10-23
Abstract
Research on sycophancy asks whether large language models (LLMs) bend towards what their users want to hear. We ask the reverse question: when an LLM is confident, consistent, and wrong, do users bend towards it? In a within-subjects experiment, 32 participants learned up to five science topics by chatting with five assistants built on the same model (GPT-5-mini). Unknown to participants, each ass
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Cite this page: Who Is Sycophantic to Whom? Confident LLMs, Human Deference, and the Collapse of Trust Calibration: the #192 most recent of 960 cs.AI papers we have recorded (as of 2026-10-22). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/who-is-sycophantic-to-whom-confident-llms-human-deference-and-the-collapse-of-tr.html
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