7 citations · 8 across the 12 of their papers we have counts for
Showing 2025Show all
3 papers · 1 filter
cs.LG2025
To Compress or Not? Pushing the Frontier of Lossless GenAI Model Weights Compression with Exponent Concentration
Zeyu Yang, Tianyi Zhang, Jianwen Xie +3
The scaling of Generative AI (GenAI) models into the hundreds of billions of parameters makes low-precision computation indispensable for efficient deployment. We argue that the fu…
cs.IR2025
CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems
Haochen Zhang, Tianyi Zhang, Junze Yin +3
Recommender systems play a pivotal role in providing relevant content to users. With the rapid development of large language models (LLMs), researchers have begun utilizing LLMs to…
cs.LG2025
Breaking the Frozen Subspace: Importance Sampling for Low-Rank Optimization in LLM Pretraining
Haochen Zhang, Junze Yin, Guanchu Wang +5
Low-rank optimization has emerged as a promising approach to enabling memory-efficient training of large language models (LLMs). Existing low-rank optimization methods typically pr…