Papers by Jingyun Wang

2 papers
Efficient and Accurate Prompt Optimization: the Benefit of Memory in Exemplar-Guided Reflection (2025.acl-long)

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Challenge: Recent work utilizes feedbacks generated from erroneous cases to guide prompt optimization . previous methods rely on computational resources and powerful GPUs .
Approach: They propose an automatic prompt engineering method that leverages feedbacks from erroneous cases to guide prompt optimization.
Outcome: The proposed method surpasses state-of-the-art methods with less steps and lower computational resources.
HAIC: Improving Human Action Understanding and Generation with Better Captions for Multi-modal Large Language Models (2025.acl-long)

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Challenge: Existing studies have shown that high-quality video captions can improve MLLMs' performance on videos involving human actions.
Approach: They propose a data annotation pipeline to collect videos featuring clear human actions from the Internet and annotate them in a standardized caption format that uses human attributes to distinguish individuals.
Outcome: The proposed pipeline combines two datasets to evaluate human action understanding.

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