2 papers
cs.CE2026
Exploring the Alignment of Generation and Understanding in Protein Structure Modeling
Junde Xu, Yuansheng Huang, Zijun Gao +5
Understanding and generation are often treated as two separate paradigms in training deep neural networks, despite the fact that both are trained with closely related objectives su…
cs.CL2023
Holmes: Towards Distributed Training Across Clusters with Heterogeneous NIC Environment
Fei Yang, Shuang Peng, Ning Sun +5
Large language models (LLMs) such as GPT-3, OPT, and LLaMA have demonstrated remarkable accuracy in a wide range of tasks. However, training these models can incur significant expe…