Wei You — accepted AI-conference papers

2026

Parameter-, Memory-, Time-Efficient Multi-Task Dense Vision Adaptation

Haiming Yao, Wei Luo, Qiyu Chen, Jianxing Liao, Wei You

AAAI 2026technical

While adapting pretrained vision models to downstream dense prediction tasks is widely used, current methods often overlook adaptation efficiency, especially in the context of multi-task learning (MTL). Although parameter-efficient fine-tuning (PEFT) methods can enhance parameter efficiency, broader

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2026

TDSS: Task Dynamic-Synergistic Skill Adaptation for Boosting Efficient and Scalable Multi-Task Learning in Dense Visual Prediction

Haiming Yao, Qiyu Chen, Wei Luo, Zheng Zhang, Jianxing Liao, Wei You

AAAI 2026technical

The transfer of knowledge from large-scale pre-trained models to diverse downstream tasks has achieved remarkable success. Beyond the traditional full fine-tuning paradigm, Parameter-Efficient Fine-Tuning (PEFT) has emerged as a more efficient model adaptation approach. However, applying existing PE

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