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Yun Chen

8 papers hereh-index 4218 citations10 works total

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

author position
  • first author1
  • middle author6

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • eess.AS2
  • cs.LG1
  • cs.SD1
same name
  • Yun Chen — 23 papers, h 7
  • Yun Chen — 8 papers, h 3
  • Yun Chen — 7 papers, h 1
  • Yun Chen — 7 papers, h 8
  • Yun Chen — 5 papers, h 3
  • Yun Chen — 5 papers, h 12

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

works on
audio synthesis 1diffusion models 1efficiency 1model pruning 1text-to-audio generation 1

From the 1 of 8 linked papers with an AI index.

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Enhancing Diffusion-Based Quantitatively Controllable Image Generation via Matrix-Form EDM and Adaptive Vicinal Training

Xin Ding, Yun Chen, Sen Zhang +5

Continuous Conditional Diffusion Model (CCDM) is a diffusion-based framework designed to generate high-quality images conditioned on continuous regression labels. Although CCDM has…

cs.CV2025

Seedream 4.0: Toward Next-generation Multimodal Image Generation

Team Seedream, :, Yunpeng Chen +48

We introduce Seedream 4.0, an efficient and high-performance multimodal image generation system that unifies text-to-image (T2I) synthesis, image editing, and multi-image compositi…

cs.CV2025

OmniText: A Training-Free Generalist for Controllable Text-Image Manipulation

Agus Gunawan, Samuel Teodoro, Yun Chen +3

Recent advancements in diffusion-based text synthesis have demonstrated significant performance in inserting and editing text within images via inpainting. However, despite the pot…

cs.CV2025

CharaConsist: Fine-Grained Consistent Character Generation

Mengyu Wang, Henghui Ding, Jianing Peng +3

In text-to-image generation, producing a series of consistent contents that preserve the same identity is highly valuable for real-world applications. Although a few works have exp…

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