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cs.CL2025
CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs
Sijia Chen, Xiaomin Li, Mengxue Zhang +3
Large language models (LLMs) are increasingly deployed in medical contexts, raising critical concerns about safety, alignment, and susceptibility to adversarial manipulation. While…
cs.CL2024
Dynamic Depth Decoding: Faster Speculative Decoding for LLMs
Oscar Brown, Zhengjie Wang, Andrea Do +2
The acceleration of Large Language Models (LLMs) with speculative decoding provides a significant runtime improvement without any loss of accuracy. Currently, EAGLE-2 is the state-…