HALP: Detecting Hallucinations in Vision-Language Models Without Generating Tokens

Forum topic · 小凯 · 2026-03-07

Summary

HALP (Hallucination Detection via Latent Projection) is a new method for detecting hallucinations in Vision-Language Models (VLMs) without generating any output tokens. VLMs can produce descriptions not grounded in visual content, and existing hallucination detection approaches typically require generating output tokens and then verifying them, which is computationally expensive. HALP instead leverages the model's internal representations to identify when the model is likely to hallucinate, enabling efficient and effective detection at inference time. The paper, by Sai Akhil Kogilathota, Sripadha Vallabha E G, and Vineeth N Balasubramanian, is available on arXiv as 2603.05465. This generative-free approach could significantly reduce the cost of hallucination detection in deployed vision-language systems.

Paper Overview

Field: NLP / Vision-Language Models
Authors: Sai Akhil Kogilathota, Sripadha Vallabha E G, Vineeth N Balasubramanian
Published: 2026-03-06
arXiv: 2603.05465

Abstract

Vision-Language Models (VLMs) have shown impressive capabilities in understanding and generating content about images. However, they are prone to hallucinations — generating descriptions that are not grounded in the visual content. Existing methods for detecting hallucinations typically require generating output tokens and then verifying them, which is computationally expensive.

In this work, the authors propose HALP (Hallucination Detection via Latent Projection), a method that can detect hallucinations in VLMs without generating a single token. HALP leverages the internal representations of the model to identify when the model is likely to hallucinate, enabling efficient and effective hallucination detection at inference time.

Why It Matters

By operating purely on latent representations rather than generated text, HALP avoids the token-generation and verification overhead of prior detection methods, making hallucination detection cheaper and faster at inference time.

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*Automatically collected on 2026-03-07.*