Papers by Yanan Lu

2 papers
Coarse-to-Fine Multimodal Information Selection for Video Speaking Style Recognition with Large Language Models (2026.findings-acl)

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Challenge: Video speaking style recognition (VSSR) aims to classify conversations into different types . integrating all multimodal data yields suboptimal results, authors say .
Approach: They propose a framework that allows users to obtain multimodal data via coarse-to-fine selection . they propose to use visual captions and textual dialogues to integrate multimodal information .
Outcome: The proposed framework outperforms existing training-free approaches and most training-based methods on multiple datasets.
TEBNER: Domain Specific Named Entity Recognition with Type Expanded Boundary-aware Network (2021.emnlp-main)

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Challenge: Existing methods to label data and identify entities require large amounts of manually annotated texts for training supervised models.
Approach: They propose a dictionary extension method which extracts new entities through the type expanded model.
Outcome: The proposed method outperforms state-of-the-art supervised systems on different types of datasets and surpasses supervised models.

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