DPL: Decoupled Prompt Learning for Vision-Language Models

no code implementations • 19 Aug 2023 • Chen Xu, Yuhan Zhu, Guozhen Zhang, Haocheng Shen, Yixuan Liao, Xiaoxin Chen, Gangshan Wu, LiMin Wang

Prompt learning has emerged as an efficient and effective approach for transferring foundational Vision-Language Models (e. g., CLIP) to downstream tasks.

Progressive Visual Prompt Learning with Contrastive Feature Re-formation

no code implementations • 17 Apr 2023 • Chen Xu, Haocheng Shen, Fengyuan Shi, Boheng Chen, Yixuan Liao, Xiaoxin Chen, LiMin Wang

To the best of our knowledge, we are the first to demonstrate the superior performance of visual prompts in V-L models to previous prompt-based methods in downstream tasks.

CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese

3 code implementations • 13 Jan 2020 • Liang Xu, Yu tong, Qianqian Dong, Yixuan Liao, Cong Yu, Yin Tian, Weitang Liu, Lu Li, Caiquan Liu, Xuanwei Zhang

In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.

Chinese Named Entity Recognition named-entity-recognition +2