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Zongyuan Zhan

2 accepted papers

2025

MoESD: Unveil Speculative Decoding's Potential for Accelerating Sparse MoE

NeurIPS 2025spotlight

Large Language Models (LLMs) have achieved remarkable success across many applications, with Mixture of Experts (MoE) models demonstrating great potential. Compared to traditional dense models, MoEs achieve better performance with less computation. Speculative decoding (SD) is a widely used techniqu…

Cited by 0SourceScholar
2020

Component Divide-and-Conquer for Real-World Image Super-Resolution

ECCV 2020poster

In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset, i.e., DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring the utility of guiding SR model with low-level image components. DRealSR establishes a new SR benchmark with diverse real…