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Before You Poll with LLMs: A Deliberative Diagnostic Framework

Paper recorded by Signals 4 on 2026-09-14 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-14 on arXiv · recorded by Signals 4 on 2026-09-15

Category: cs.AI · 人工智能 · first seen 2026-09-15

Abstract

Can LLMs reason through new information like humans, or do they merely retrieve cached opinions? This is critical for silicon sampling, where LLM personas simulate public opinion at scale. Current evaluations test only whether personas hold the right opinions -- a static snapshot. But opinion research increasingly depends on dynamic fidelity: whether personas update beliefs in response to new argu

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#74 most recent of 300 cs.AI papers we have recorded · ↑ newer: K-Bench: a clinically calibrated benchmark for evaluating large langua · ↓ older: Per-Matrix Optimality Is Not Enough: Three-Level Optimization for Low-
Cite this page: Before You Poll with LLMs: A Deliberative Diagnostic Framework: the #74 most recent of 300 cs.AI papers we have recorded (as of 2026-09-14). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/before-you-poll-with-llms-a-deliberative-diagnostic-framework.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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