Papers by Qilin Sun

1 papers
Towards Fine-grained Audio Captioning with Multimodal Contextual Fusion (2026.acl-long)

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Challenge: Existing methods for audio captioning lack fine-grained detail and contextual accuracy due to limited unimodal or superficial information.
Approach: They propose a two-stage automated pipeline that uses pretrained models to extract contextual cues from video . a large language model synthesizes these inputs to generate detailed and context-aware captions .
Outcome: The proposed method is scalable and generates detailed and context-aware captions on large-scale audio datasets.

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