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Wei Liu

15 papers hereh-index 477 citations16 works total

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

author position
  • first author1
  • middle author9
  • last author2

Across the 12 of 15 papers where every author was matched, so the position is known.

fields
  • cs.CV8
  • cs.LG4
  • cs.AI1
  • cs.CL1
  • cs.CR1
same name
  • Wei Liu — 30 papers, h 12
  • Wei Liu — 17 papers, h 3
  • Wei Liu — 11 papers, h 10
  • Wei Liu — 10 papers, h 2
  • Wei Liu — 9 papers, h 1
  • Wei Liu — 9 papers, h 3

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

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective

Xiaoyi Jiang, Jingyuan Li, Yixuan Jiang +4

Existing methods mainly adapt pretrained autoregressive (AR) language models to masked diffusion, whereas we directly adapt them to uniform-noise diffusion, where every token remai…

cs.LG2026

Mean-to-Score Discrete Diffusion: Posterior-Mean Denoisers for Score Entropy

Jingyuan Li, Xiaoyi Jiang, Yixuan Jiang +4

Score Entropy Discrete Diffusion (SEDD) parameterizes discrete reverse processes with unconstrained positive score ratios. While positivity guarantees nonnegative reverse jump rate…

cs.LG2026

Neural Continuous-Time Markov Chain: Discrete Diffusion via Decoupled Jump Timing and Direction

Jingyuan Li, Xiaoyi Jiang, Fukang Wen +5

Discrete diffusion models based on continuous-time Markov chains (CTMCs) have shown strong performance on language and discrete data generation, yet existing approaches typically p…

cs.LG2026

LoDAdaC: a unified local training-based decentralized framework with adaptive gradients and compressed communication

Wei Liu, Anweshit Panda, Ujwal Pandey +5

In the decentralized distributed learning, achieving fast convergence and low communication cost is essential for scalability and high efficiency. Adaptive gradient methods, such a…

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