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arXiv Computation and Language By Eli Schwartz

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

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The paper describes a system for the SHROOM-Visions 2026 shared task on character-level VLM hallucination detection. It combines a small 4‑B‑parameter VLM fine‑tuned as a per‑token classifier that uses a two‑token feature from its hidden states with a large ~400‑B zero‑shot VLM judge at prediction time, both leveraging OCR of visible in‑image text. Using synthetic hallucination data from the large model for ensemble diversity and validation‑based selection of feature layer, training data, and OCR grounding, the entry achieved competitive results across multiple languages.

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