29 citations · 47 across the 18 of their papers we have counts for
5 papers · 1 filter
Instruct Me More! Random Prompting for Visual In-Context Learning
Jiahao Zhang, Bowen Wang, Liangzhi Li +2
Large-scale models trained on extensive datasets, have emerged as the preferred approach due to their high generalizability across various tasks. In-context learning (ICL), a popul…
Improving Facade Parsing with Vision Transformers and Line Integration
Bowen Wang, Jiaxing Zhang, Ran Zhang +3
Facade parsing stands as a pivotal computer vision task with far-reaching applications in areas like architecture, urban planning, and energy efficiency. Despite the recent success…
IncreLoRA: Incremental Parameter Allocation Method for Parameter-Efficient Fine-tuning
Feiyu Zhang, Liangzhi Li, Junhao Chen +3
With the increasing size of pre-trained language models (PLMs), fine-tuning all the parameters in the model is not efficient, especially when there are a large number of downstream…
CARE-MI: Chinese Benchmark for Misinformation Evaluation in Maternity and Infant Care
Tong Xiang, Liangzhi Li, Wangyue Li +4
The recent advances in natural language processing (NLP), have led to a new trend of applying large language models (LLMs) to real-world scenarios. While the latest LLMs are astoni…
Learning Bottleneck Concepts in Image Classification
Bowen Wang, Liangzhi Li, Yuta Nakashima +1
Interpreting and explaining the behavior of deep neural networks is critical for many tasks. Explainable AI provides a way to address this challenge, mostly by providing per-pixel…