Papers by Heyu Huang

2 papers
EchoMLLM: Incentivizing Echocardiographic Video Understanding with Keyframe Grounding and Report Generation (2026.findings-acl)

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Challenge: Echocardiography analysis requires a dual capability: rigorous quantitative keyframe localization and comprehensive qualitative synthesis.
Approach: They propose a unified framework designed for real-world echocardiography video understanding.
Outcome: a new framework is designed to support real-world echocardiography video understanding . it reduces temporal grounding errors by up to 76% and improves report generation quality by 65% .
Migician: Revealing the Magic of Free-Form Multi-Image Grounding in Multimodal Large Language Models (2025.findings-acl)

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Challenge: Existing MLLMs still struggle to achieve precise grounding in multi-image scenarios.
Approach: They propose a Chain-of-Thought framework that integrates single-image grounding with multi-image comprehension to address this challenge.
Outcome: The proposed model outperforms existing models in multi-image grounding tasks by 24.94% and surpasses larger 70B models.

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