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Jiacheng Ye

The University of Hong Kong

26 papers hereh-index 212.3k citations30 works total

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

author position
  • first author12
  • middle author12
  • last author1

Across the 25 of 26 papers where every author was matched, so the position is known.

fields
  • cs.CL20
  • cs.CV2
  • cs.LG2
  • cs.DS1
  • cs.SE1
affiliations
  • The University of Hong Kong
Homepage
same name
  • Jiacheng Ye — 2 papers
  • Jiacheng Ye — 1 paper, h 1

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
20192026
most citedCompositional Exemplars for In-context Learning

24 citations · 75 across the 24 of their papers we have counts for

collaborators
Showing 2026Show all

4 papers · 1 filter

cs.SE2026

How Should Diffusion Language Models Edit Code?

Xijia Tao, Ziru Liu, Shansan Gong +7

Code editing requires a model to decide where to make changes, generate the new content, and preserve everything else. We study how masked diffusion language models divide these re…

cs.CL2026

DreamReasoner-8B: Block-Size Curriculum Learning for Diffusion Reasoning Models

Zirui Wu, Lin Zheng, Jiacheng Ye +5

Block diffusion language models accelerate decoding through parallel block-wise denoising, yet whether they can be reliably scaled for long chain-of-thought (CoT) reasoning remains…

cs.CL2026

DreamOn: Diffusion Language Models For Code Infilling Beyond Fixed-size Canvas

Zirui Wu, Lin Zheng, Zhihui Xie +8

Diffusion Language Models (DLMs) present a compelling alternative to autoregressive models, offering flexible, any-order infilling without specialized prompting design. However, th…

cs.CV2026

Dream-VL & Dream-VLA: Open Vision-Language and Vision-Language-Action Models with Diffusion Language Model Backbone

Jiacheng Ye, Shansan Gong, Jiahui Gao +6

While autoregressive Large Vision-Language Models (VLMs) have achieved remarkable success, their sequential generation often limits their efficacy in complex visual planning and dy…

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