13 citations · 18 across the 14 of their papers we have counts for
4 papers · 1 filter
LLM in a flash: Efficient Large Language Model Inference with Limited Memory
Keivan Alizadeh, Iman Mirzadeh, Dmitry Belenko +5
Large language models (LLMs) are central to modern natural language processing, delivering exceptional performance in various tasks. However, their substantial computational and me…
Streaming Anchor Loss: Augmenting Supervision with Temporal Significance
Utkarsh Oggy Sarawgi, John Berkowitz, Vineet Garg +5
Streaming neural network models for fast frame-wise responses to various speech and sensory signals are widely adopted on resource-constrained platforms. Hence, increasing the lear…
Do Compressed LLMs Forget Knowledge? An Experimental Study with Practical Implications
Duc N. M Hoang, Minsik Cho, Thomas Merth +2
Compressing Large Language Models (LLMs) often leads to reduced performance, especially for knowledge-intensive tasks. In this work, we dive into how compression damages LLMs' inhe…
eDKM: An Efficient and Accurate Train-time Weight Clustering for Large Language Models
Minsik Cho, Keivan A. Vahid, Qichen Fu +5
Since Large Language Models or LLMs have demonstrated high-quality performance on many complex language tasks, there is a great interest in bringing these LLMs to mobile devices fo…