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Vroom-Vroom at SHROOM-Visions: A Multi-Judge Committee for Detecting Hallucinated Spans in Vision-Language Outputs

Paper recorded by Signals 4 on 2026-09-15 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-09-15 on arXiv · recorded by Signals 4 on 2026-09-16

Category: cs.CL · 自然语言处理 · first seen 2026-09-16

Abstract

This paper describes our submission to the SHROOM-Visions shared task on detecting and classifying hallucinated character spans in vision-language model outputs across four languages. We employ several fine-tuned vision-language models as independent annotators and combine their span predictions through character-level majority voting, and additionally explore activation probes. The approach ranks

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#30 most recent of 186 cs.CL papers we have recorded · ↑ newer: ECHO: A Matched-Contrast Benchmark for Context-Sensitive Turn-Taking i · ↓ older: Towards Detecting AI-Assisted Responses in Online Surveys
Cite this page: Vroom-Vroom at SHROOM-Visions: A Multi-Judge Committee for Detecting Hallucinated Spans in Vision-Language Outputs: the #30 most recent of 186 cs.CL papers we have recorded (as of 2026-09-15). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/vroom-vroom-at-shroom-visions-a-multi-judge-committee-for-detecting-hallucinated.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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