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arXiv AI By Toqeer Ehsan, Nico Penttil\"a, Richard Schmidt, Arash Hajikhani, Victoria Palacin

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

Read the original on arXiv AI →

The paper reports a submission to the SHROOM-Visions shared task, aiming to detect and classify hallucinated character spans in vision‑language model outputs across four languages. The authors use multiple fine‑tuned vision‑language models as independent annotators, combine their predictions via character‑level majority voting, and also investigate activation probes. Their method achieved first place in three of the four languages and consistently ranked on the podium for all languages and metrics, with analysis showing that model disagreement mirrors human annotator disagreement.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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