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cs.CL2026
Beyond Steering Vector: Flow-based Activation Steering for Inference-Time Intervention
Zehao Jin, Ruixuan Deng, Junran Wang +2
Activation steering has emerged as a promising alternative for controlling language-model behavior at inference time by modifying intermediate representations while keeping model p…
cs.CL2025
EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
Yuhui Li, Fangyun Wei, Chao Zhang +1
The sequential nature of modern LLMs makes them expensive and slow, and speculative sampling has proven to be an effective solution to this problem. Methods like EAGLE perform auto…
cs.CL2024
EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees
Yuhui Li, Fangyun Wei, Chao Zhang +1
Inference with modern Large Language Models (LLMs) is expensive and time-consuming, and speculative sampling has proven to be an effective solution. Most speculative sampling metho…