# Hallucination Localization in Video Captioning

arXiv: https://arxiv.org/abs/2510.25225 · HTML: https://mlsanity.com/paper/2510.25225/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Oct 2025.

## Built on by (most cited first, 2 of 2)

- [DetailVerifyBench: A Benchmark for Dense Hallucination Localization in Long Image Captions](https://mlsanity.com/paper/2604.05623/) (2026)
- [CodecCap: High-Fidelity Codec-Inspired Residual Modeling for Dense Video Captioning](https://mlsanity.com/paper/2605.26967/) (2026)

## Abstract (arXiv)

We propose a novel task, hallucination localization in video captioning, which aims to identify hallucinations in video captions at the span level (i.e. individual words or phrases). This allows for a more detailed analysis of hallucinations compared to existing sentence-level hallucination detection task. To establish a benchmark for hallucination localization, we construct HLVC-Dataset, a carefully curated dataset created by manually annotating 1,167 video-caption pairs from VideoLLM-generated captions. We further implement a VideoLLM-based baseline method and conduct quantitative and qualitative evaluations to benchmark current performance on hallucination localization.