68 citations · 68 across the 6 of their papers we have counts for
4 papers · 1 filter
Low-Precision Training of Large Language Models: Methods, Challenges, and Opportunities
Zhiwei Hao, Jianyuan Guo, Li Shen +6
Large language models (LLMs) have achieved impressive performance across various domains. However, the substantial hardware resources required for their training present a signific…
Joint Input and Output Coordination for Class-Incremental Learning
Shuai Wang, Yibing Zhan, Yong Luo +4
Incremental learning is nontrivial due to severe catastrophic forgetting. Although storing a small amount of data on old tasks during incremental learning is a feasible solution, c…
Federated Learning with Only Positive Labels by Exploring Label Correlations
Xuming An, Dui Wang, Li Shen +5
Federated learning aims to collaboratively learn a model by using the data from multiple users under privacy constraints. In this paper, we study the multi-label classification pro…
Confronting Reward Overoptimization for Diffusion Models: A Perspective of Inductive and Primacy Biases
Ziyi Zhang, Sen Zhang, Yibing Zhan +3
Bridging the gap between diffusion models and human preferences is crucial for their integration into practical generative workflows. While optimizing downstream reward models has…