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cs.CL2026
Top-Theta Attention: Sparsifying Transformers by Compensated Thresholding
Konstantin Berestizshevsky, Renzo Andri, Lukas Cavigelli
We present Top-Theta (Top-) Attention, a training-free method for sparsifying transformer attention during inference. Our key insight is that static, per-head thresholds can be…
cs.CL2026
SSSD: Simply-Scalable Speculative Decoding
Michele Marzollo, Jiawei Zhuang, Niklas Roemer +3
Speculative Decoding has emerged as a popular technique for accelerating inference in Large Language Models. However, most existing approaches yield only modest improvements in pro…