2 citations · 3 across the 6 of their papers we have counts for
4 papers · 1 filter
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
Enshu Liu, Junyi Zhu, Zinan Lin +6
The rapid advancement of large language models (LLMs) has led to architectures with billions to trillions of parameters, posing significant deployment challenges due to their subst…
FastMem: Fast Memorization of Prompt Improves Context Awareness of Large Language Models
Junyi Zhu, Shuochen Liu, Yu Yu +6
Large language models (LLMs) excel in generating coherent text, but they often struggle with context awareness, leading to inaccuracies in tasks requiring faithful adherence to pro…
Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction
Jiayang Shi, Junyi Zhu, Daniel M. Pelt +2
Computed Tomography (CT) is pivotal in industrial quality control and medical diagnostics. Sparse-view CT, offering reduced ionizing radiation, faces challenges due to its under-sa…
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin +8
Diffusion Models (DM) and Consistency Models (CM) are two types of popular generative models with good generation quality on various tasks. When training DM and CM, intermediate we…