Papers by Erhu Feng

1 papers
HCSpec: Two-Tier Horizontal Cascade Speculative Decoding for High-Efficiency Large Language Model Inference (2026.acl-long)

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Challenge: Existing approaches to decode large language models adopt a homogeneous architecture . autoregressive decoding is a bottleneck because tokens must be generated sequentially .
Approach: They propose a framework that organizes heterogeneous position-specialized draft modules into a horizontal cascade.
Outcome: The proposed framework outperforms the current state-of-the-art (EAGLE3) and achieves 3.72x acceleration over vanilla decoding.

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