13 citations · 13 across the 3 of their papers we have counts for
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cs.CL2026
UniVer: A Unified Perspective for Multi-step and Multi-draft Speculative Decoding
Yepeng Weng, Qiao Hu, Takehisa Yairi
Speculative decoding accelerates Large Language Models via draft-then-verify, where verification can be framed as an Optimal Transport (OT) problem. Existing approaches typically h…
cs.CL2025
Traversal Verification for Speculative Tree Decoding
Yepeng Weng, Qiao Hu, Xujie Chen +5
Speculative decoding is a promising approach for accelerating large language models. The primary idea is to use a lightweight draft model to speculate the output of the target mode…
cs.CL2025
CORAL: Learning Consistent Representations across Multi-step Training with Lighter Speculative Drafter
Yepeng Weng, Dianwen Mei, Huishi Qiu +4
Speculative decoding is a powerful technique that accelerates Large Language Model (LLM) inference by leveraging a lightweight speculative draft model. However, existing designs su…