7 citations · 10 across the 9 of their papers we have counts for
3 papers · 1 filter
Active Learning with Low-Rank Structure for Data Selection
Vincent Cohen-Addad, Sasidhar Kunapuli, Vahab Mirrokni +3
In the data selection problem, the objective is to choose a small, representative subset of data that can be used to efficiently train a machine learning model. Sener and Savarese…
GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
Alireza Dadgarnia, Soroush Tabesh, Mahdi Nikdan +4
Quantization has become a standard tool for efficient LLM deployment, especially for local inference, where models are now routinely served at 2-3 bits per parameter. The state of…
ECO: Quantized Training without Full-Precision Master Weights
Mahdi Nikdan, Amir Zandieh, Dan Alistarh +1
Quantization has significantly improved the compute and memory efficiency of Large Language Model (LLM) training. However, existing approaches still rely on accumulating their upda…