2 citations · 2 across the 4 of their papers we have counts for
4 papers
ELBA-Bench: An Efficient Learning Backdoor Attacks Benchmark for Large Language Models
Xuxu Liu, Siyuan Liang, Mengya Han +5
Generative large language models are crucial in natural language processing, but they are vulnerable to backdoor attacks, where subtle triggers compromise their behavior. Although…
PartSeg: Few-shot Part Segmentation via Part-aware Prompt Learning
Mengya Han, Heliang Zheng, Chaoyue Wang +4
In this work, we address the task of few-shot part segmentation, which aims to segment the different parts of an unseen object using very few labeled examples. It is found that lev…
Not All Instances Contribute Equally: Instance-adaptive Class Representation Learning for Few-Shot Visual Recognition
Mengya Han, Yibing Zhan, Yong Luo +4
Few-shot visual recognition refers to recognize novel visual concepts from a few labeled instances. Many few-shot visual recognition methods adopt the metric-based meta-learning pa…
Leveraging GAN Priors for Few-Shot Part Segmentation
Mengya Han, Heliang Zheng, Chaoyue Wang +3
Few-shot part segmentation aims to separate different parts of an object given only a few annotated samples. Due to the challenge of limited data, existing works mainly focus on le…