84 citations · 111 across the 8 of their papers we have counts for
8 papers
Denser Better: Limits of On-Policy Self-Distillation for Continual Post-Training
Meng Wang, Haohan Zhao, Wenzhuo Liu +7
Continual post-training enables foundation models to acquire new knowledge while preserving existing capabilities. Recent work suggests that on-policy learning can mitigate forgett…
Self-Consolidation for Self-Evolving Agents
Hongzhuo Yu, Fei Zhu, Guo-Sen Xie +1
While large language model (LLM) agents have demonstrated impressive problem-solving capabilities, they typically operate as static systems, lacking the ability to evolve through l…
CDIMC-net: Cognitive Deep Incomplete Multi-view Clustering Network
Jie Wen, Zheng Zhang, Yong Xu +3
In recent years, incomplete multi-view clustering, which studies the challenging multi-view clustering problem on missing views, has received growing research interests. Although a…
Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation
Jie Liu, Yanqi Bao, Guo-Sen Xie +3
The key challenge for few-shot semantic segmentation (FSS) is how to tailor a desirable interaction among support and query features and/or their prototypes, under the episodic tra…
MSDN: Mutually Semantic Distillation Network for Zero-Shot Learning
Shiming Chen, Ziming Hong, Guo-Sen Xie +5
The key challenge of zero-shot learning (ZSL) is how to infer the latent semantic knowledge between visual and attribute features on seen classes, and thus achieving a desirable kn…
HSVA: Hierarchical Semantic-Visual Adaptation for Zero-Shot Learning
Shiming Chen, Guo-Sen Xie, Yang Liu +5
Zero-shot learning (ZSL) tackles the unseen class recognition problem, transferring semantic knowledge from seen classes to unseen ones. Typically, to guarantee desirable knowledge…