Papers by Qianli Xing

2 papers
From Coarse to Fine: A Multi-Granularity Multimodal Framework for Teacher Sentiment Analysis (2026.findings-acl)

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Challenge: Existing approaches to teacher sentiment analysis treat it as a static label . current approaches fail to capture structured heterogeneity of classroom expressions .
Approach: They propose a coarse-to-fine multimodal framework that decomposes teacher sentiment into three granularities and employ CLS-guided cross-modal attention to recover effective signals from regulated displays.
Outcome: The proposed framework outperforms state-of-the-art models on T-MED and CMU-MOSEI.
Human-Agent Collaborative Paper-to-Page Crafting (2026.findings-acl)

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Challenge: Existing approaches to create project pages from academic papers have focused on static slides and posters, but the dynamic nature of webpages remains an unaddressed challenge.
Approach: They propose a novel multi-agent system that deconstructs paper-to-page creation into a coarse-to fine pipeline from narrative planning to multimodal content generation and interactive rendering.
Outcome: The proposed system generates high-quality, visually appealing pages in under 15 minutes for less than $0.1 .

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