3 papers
cs.LG2026
Importance-Guided Basis Selection for Low-Rank Decomposition of Large Language Models
Daniel Agyei Asante, Ernie Chang, Yang Li
Low-rank decomposition is a compelling approach for compressing large language models, but its effectiveness hinges on selecting which singular-vector bases to retain for a target…
cs.LG2026
Decomposed Trust: Privacy, Adversarial Robustness, Ethics, and Fairness in Low-Rank LLMs
Daniel Agyei Asante, Md Mokarram Chowdhury, Yang Li
Large language models (LLMs) have driven major advances across domains, yet their massive size hinders deployment in resource-constrained settings. Low-rank factorization addresses…
cs.LG2026
IMPACT: Importance-Aware Activation Space Reconstruction
Md Mokarram Chowdhury, Daniel Agyei Asante, Ernie Chang +1
Large language models (LLMs) achieve strong performance across diverse domains but remain difficult to deploy in resource-constrained environments due to their size. Low-rank compr…