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Ye Tian

4 papers here

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

author position
  • middle author3

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.CL1
  • eess.IV1
ORCID 0000-0002-0981-6677
same name
  • Ye Tian — 22 papers
  • Ye Tian — 5 papers, h 10
  • Ye Tian — 5 papers, h 6
  • Ye Tian — 4 papers, h 18
  • Ye Tian — 4 papers
  • Ye Tian — 3 papers

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

most citedSIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models

1 citations · 2 across the 4 of their papers we have counts for

collaborators

4 papers

eess.IV2025

A Feasibility Study of Task-Based fMRI at 0.55 T

Parsa Razmara, Takfarinas Medani, Anand A. Joshi +6

0.55T MRI offers advantages compared to conventional field strengths, including reduced susceptibility artifacts and better compatibility with simultaneous EEG recordings. However,…

cs.CV2025

Training-free Diffusion Acceleration with Bottleneck Sampling

Ye Tian, Xin Xia, Yuxi Ren +6

Diffusion models have demonstrated remarkable capabilities in visual content generation but remain challenging to deploy due to their high computational cost during inference. This…

cs.CL2024★ 1 cited

SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models

Dian Yu, Baolin Peng, Ye Tian +3

There is a growing trend of teaching large language models (LLMs) to solve mathematical problems through coding. Existing studies primarily focus on prompting powerful, closed-sour…

cs.CV2024★ 1 cited

AGLLDiff: Guiding Diffusion Models Towards Unsupervised Training-free Real-world Low-light Image Enhancement

Yunlong Lin, Tian Ye, Sixiang Chen +6

Existing low-light image enhancement (LIE) methods have achieved noteworthy success in solving synthetic distortions, yet they often fall short in practical applications. The limit…

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