Papers by Yuli Chen

2 papers
VideoQA-TA: Temporal-Aware Multi-Modal Video Question Answering (2025.coling-main)

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Challenge: Existing methods for video question answering align visual or textual features directly with large language models, limiting the deep semantic association between modalities and hindering a comprehensive understanding of interactions within spatial and temporal contexts.
Approach: They propose a temporal-aware framework for multi-modal video question answering that aligns videos and questions at fine-grained levels.
Outcome: The proposed framework improves reasoning ability and accuracy of videoQA by aligning videos and questions at fine-grained levels.
Beyond A Fixed Seal: Adaptive Stealing Watermark in Large Language Models (2026.findings-acl)

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Challenge: Existing detection methods for large language models rely on fixed strategies to steal watermarks.
Approach: They propose a novel steal-based watermark algorithm that derives watermark information from watermarked texts to craft highly targeted adversarial attacks.
Outcome: The proposed system significantly increases steal efficiency against target watermarks under identical conditions.

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