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Two-Token Features and Small-Large Ensembles for VLM Hallucination Detection

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

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

Category: cs.CL · 自然语言处理 · first seen 2026-09-10

Abstract

We present our system for the SHROOM-Visions 2026 shared task on character-level VLM hallucination detection. A small ($4$B-parameter) VLM is fine-tuned as a per-token classifier reading a two-token feature from its own hidden states, and is ensembled with a $\sim$400B zero-shot VLM judge at prediction time. Both components see off-the-shelf OCR of any visible in-image text. We use synthetic hallu

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#87 most recent of 186 cs.CL papers we have recorded · ↑ newer: DiSCo: A Distribution-First Steering and Cultural Prior Evaluation Fra · ↓ older: LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation
Cite this page: Two-Token Features and Small-Large Ensembles for VLM Hallucination Detection: the #87 most recent of 186 cs.CL papers we have recorded (as of 2026-09-09). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/two-token-features-and-small-large-ensembles-for-vlm-hallucination-detection.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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