2 papers
cs.CL2026
PrefixMemory-Tuning: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention
Haonan Wang, Brian Chen, Siquan Li +4
Parameter-Efficient Fine-Tuning (PEFT) methods have become crucial for rapidly adapting large language models (LLMs) to downstream tasks. Prefix-Tuning, an early and effective PEFT…
cs.RO2025
A Comprehensive LLM-powered Framework for Driving Intelligence Evaluation
Shanhe You, Xuewen Luo, Xinhe Liang +3
Evaluation methods for autonomous driving are crucial for algorithm optimization. However, due to the complexity of driving intelligence, there is currently no comprehensive evalua…