Papers by Haolin He
FineLAP: Taming Heterogeneous Supervision for Fine-grained Language-Audio Pretraining (2026.acl-long)
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| Challenge: | Existing audio-language models excel at clip-level understanding but struggle with frame-level tasks. |
| Approach: | They propose a novel training paradigm that advances both clip- and frame-level alignment in CLAP with heterogeneous data. |
| Outcome: | The proposed training paradigm improves both clip- and frame-level alignment in CLAP with heterogeneous data. |
APEX: Learning Adaptive Priorities for Multi-Objective Alignment in Vision-Language Generation (2026.findings-acl)
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Dongliang Chen, Xinlin Zhuang, Junjie Xu, Luojian Xie, Zehui Wang, Jiaxi Zhuang, Haolin Yang, Liang Dou, Xiao He, Xingjiao Wu, Ying Qian
| Challenge: | APEX optimizes for text-to-image generation by combining learning potential, conflict penalty, and progress need. |
| Approach: | They propose an algorithm that stabilizes heterogeneous rewards and dynamically schedules objectives . they propose a method that achieves better Pareto trade-offs across four heterogenous objectives based on P3 Adaptive Priorities . |
| Outcome: | The proposed algorithm achieves better pareto trade-offs across four heterogeneous objectives while maintaining competitive OCR accuracy. |