2 papers
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.CR2025
Defending Large Language Models Against Attacks With Residual Stream Activation Analysis
Amelia Kawasaki, Andrew Davis, Houssam Abbas
The widespread adoption of Large Language Models (LLMs), exemplified by OpenAI's ChatGPT, brings to the forefront the imperative to defend against adversarial threats on these mode…