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researcher

Yang Sui

Rice University

20 papers hereh-index 131.1k citations34 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author7
  • middle author12

Across the 19 of 20 papers where every author was matched, so the position is known.

fields
  • cs.CV9
  • cs.LG4
  • cs.CL3
  • cs.CR1
  • cs.GR1
  • eess.IV1
affiliations
  • Rice University
same name
  • Yang Sui — 6 papers, h 5
  • Yang Sui — 6 papers, h 1
  • Yang Sui — 5 papers, h 2
  • Yang Sui — 1 paper, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212026
most citedCHIP: CHannel Independence-based Pruning for Compact Neural Networks

25 citations · 48 across the 19 of their papers we have counts for

collaborators
Showing 2024Show all

4 papers · 1 filter

cs.LG2024

MoE-I2: Compressing Mixture of Experts Models through Inter-Expert Pruning and Intra-Expert Low-Rank Decomposition

Cheng Yang, Yang Sui, Jinqi Xiao +7

The emergence of Mixture of Experts (MoE) LLMs has significantly advanced the development of language models. Compared to traditional LLMs, MoE LLMs outperform traditional LLMs by…

cs.CV2024★ 1 cited

BitsFusion: 1.99 bits Weight Quantization of Diffusion Model

Yang Sui, Yanyu Li, Anil Kag +7

Diffusion-based image generation models have achieved great success in recent years by showing the capability of synthesizing high-quality content. However, these models contain a…

cs.CR2024★ 4 cited

DisDet: Exploring Detectability of Backdoor Attack on Diffusion Models

Yang Sui, Huy Phan, Jinqi Xiao +6

In the exciting generative AI era, the diffusion model has emerged as a very powerful and widely adopted content generation and editing tool for various data modalities, making the…

cs.CV2024

ELRT: Efficient Low-Rank Training for Compact Convolutional Neural Networks

Yang Sui, Miao Yin, Yu Gong +3

Low-rank compression, a popular model compression technique that produces compact convolutional neural networks (CNNs) with low rankness, has been well-studied in the literature. O…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.