4 papers
Do LLMs Have Values? A Quantitative Analysis and Alignment Framework for Values in Large Language Models
Keqing Zhang, Jingyu Chen, Yufan Liu +6
As Large Language Models (LLMs) increasingly handle complex subjective tasks, aligning their intentions and behaviors with human values has become a critical scientific challenge.…
Beyond Independence: Learning Correlated Views for Variational Incomplete Multi-View Clustering
Zheming Xu, Aiyue Tang, Shidi Chen +4
Incomplete multi-view clustering (IMVC) aims to uncover shared cluster structures from data with partially observed views. Although recent imputation-free methods based on variatio…
Progressive Reasoning with Primitive Correction for Compositional Zero-Shot Learning
Ziyi Chen, Haoyan Shi, Sunhan Xu +1
Compositional Zero-Shot Learning (CZSL) aims to combine known attributes and objects as primitives for recognizing previously unseen attribute-object pairs. Prior works either pred…
Query-aware Hub Prototype Learning for Few-Shot 3D Point Cloud Semantic Segmentation
YiLin Zhou, Lili Wei, Zheming Xu +2
Few-shot 3D point cloud semantic segmentation (FS-3DSeg) aims to segment novel classes with only a few labeled samples. However, existing metric-based prototype learning methods ge…