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| Hauptverfasser: | , , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2510.25225 |
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| _version_ | 1866909875764723712 |
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| author | Nakada, Shota Saito, Kazuhiro Ishikawa, Yuchi Munakata, Hokuto Komatsu, Tatsuya Kondo, Masayoshi |
| author_facet | Nakada, Shota Saito, Kazuhiro Ishikawa, Yuchi Munakata, Hokuto Komatsu, Tatsuya Kondo, Masayoshi |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2510_25225 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hallucination Localization in Video Captioning Nakada, Shota Saito, Kazuhiro Ishikawa, Yuchi Munakata, Hokuto Komatsu, Tatsuya Kondo, Masayoshi Multimedia 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. |
| title | Hallucination Localization in Video Captioning |
| topic | Multimedia |
| url | https://arxiv.org/abs/2510.25225 |