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Searching for "Harmful Refusal": A Psychometric Audit of an AI Safety Benchmark

Paper recorded by Signals 4 on 2026-10-08 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-08 on arXiv · recorded by Signals 4 on 2026-10-09

Category: cs.AI · 人工智能 · first seen 2026-10-09

Abstract

Safety benchmarks typically report one overall score for a suite of datasets, each of which may target one or more safety-related attributes, so models with similar overall scores can have very different attribute profiles. Comparing models is more tractable at the level of individual attributes, yet it is often unclear whether even a single dataset's scores isolate any single attribute. One plaus

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#370 most recent of 960 cs.AI papers we have recorded · ↑ newer: Predicting Alignment Generalization with Value Representations · ↓ older: LeWAM: A JEPA World Action Model with Diffusion-Steering-Based MPC
Cite this page: Searching for "Harmful Refusal": A Psychometric Audit of an AI Safety Benchmark: the #370 most recent of 960 cs.AI papers we have recorded (as of 2026-10-08). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/searching-for-harmful-refusal-a-psychometric-audit-of-an-ai-safety-benchmark.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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