4 papers
TrainSDC: Characterizing and Mitigating Silent Data Corruption in Large Language Model Training
Zhipeng Xia, Haotian Xu, Siyu Yun +4
LLM training is increasingly vulnerable to silent data corruption (SDC), yet existing protection methods largely treat Transformer computations uniformly because their vulnerabilit…
SafeSpec: Fast and Safe LLM via Dynamic Reflective Sampling
Haotian Xu, Zeyang Zhang, Linbao Li +3
Speculative inference accelerates large language model (LLM) decoding but provides no inherent safety guarantees. Existing safety defenses are largely incompatible with speculative…
SilentStriker:Toward Stealthy Bit-Flip Attacks on Large Language Models
Haotian Xu, Qingsong Peng, Jie Shi +3
The rapid adoption of large language models (LLMs) in critical domains has spurred extensive research into their security issues. While input manipulation attacks (e.g., prompt inj…
Reconfigurable Frequency Multipliers Based on Complementary Ferroelectric Transistors
Haotian Xu, Jianyi Yang, Cheng Zhuo +3
Frequency multipliers, a class of essential electronic components, play a pivotal role in contemporary signal processing and communication systems. They serve as crucial building b…