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cs.LG2025
EQuARX: Efficient Quantized AllReduce in XLA for Distributed Machine Learning Acceleration
Ibrahim Ahmed, Clemens Schaefer, Gil Tabak +5
While Large Language Models (LLMs) have become highly influential, their enormous scale presents significant deployment challenges. Efficiently serving these models typically requi…
cs.LG2024
On Training a Neural Network to Explain Binaries
Alexander Interrante-Grant, Andy Davis, Heather Preslier +1
In this work, we begin to investigate the possibility of training a deep neural network on the task of binary code understanding. Specifically, the network would take, as input, fe…