1 citations · 1 across the 4 of their papers we have counts for
4 papers
Switch-KD: Visual-Switch Knowledge Distillation for Vision-Language Models
Haoyi Sun, Xiaoxiao Wang, Ning Mao +5
Vision-Language Models (VLMs) have shown remarkable capabilities in joint vision-language understanding, but their large scale poses significant challenges for deployment in resour…
Sketching the Readout of Large Language Models for Scalable Data Attribution and Valuation
Yide Ran, Jianwen Xie, Minghui Wang +4
Data attribution and valuation are critical for understanding data-model synergy for Large Language Models (LLMs), yet existing gradient-based methods suffer from scalability chall…
Contextual Knowledge Learning For Dialogue Generation
Wen Zheng, Natasa Milic-Frayling, Ke Zhou
Incorporating conversational context and knowledge into dialogue generation models has been essential for improving the quality of the generated responses. The context, comprising…
Towards Generalizable Graph Contrastive Learning: An Information Theory Perspective
Yige Yuan, Bingbing Xu, Huawei Shen +4
Graph contrastive learning (GCL) emerges as the most representative approach for graph representation learning, which leverages the principle of maximizing mutual information (Info…