113 citations · 191 across the 22 of their papers we have counts for
3 papers · 1 filter
TruncFormer: Private LLM Inference Using Only Truncations
Patrick Yubeaton, Jianqiao Cambridge Mo, Karthik Garimella +4
Private inference (PI) serves an important role in guaranteeing the privacy of user data when interfacing with proprietary machine learning models such as LLMs. However, PI remains…
ReLU's Revival: On the Entropic Overload in Normalization-Free Large Language Models
Nandan Kumar Jha, Brandon Reagen
LayerNorm is a critical component in modern large language models (LLMs) for stabilizing training and ensuring smooth optimization. However, it introduces significant challenges in…
AERO: Entropy-Guided Framework for Private LLM Inference
Nandan Kumar Jha, Brandon Reagen
Privacy-preserving computation enables language model inference directly on encrypted data yet suffers from prohibitive latency and communication overheads, primarily due to nonlin…