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researcher

Bowen Zhou

17 papers hereh-index 7189 citations19 works total

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

author position
  • middle author7
  • last author10

Across the 17 of 17 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.AI2
  • cs.IR1
  • cs.LG1
same name
  • Bowen Zhou — 39 papers, h 19
  • Bowen Zhou — 35 papers, h 47
  • Bowen Zhou — 25 papers, h 17
  • Bowen Zhou — 25 papers, h 9
  • Bowen Zhou — 21 papers, h 7
  • Bowen Zhou — 19 papers, h 8

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
20232026
most citedLMD: Faster Image Reconstruction with Latent Masking Diffusion

3 citations · 8 across the 16 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

Emotion-Director: Bridging Affective Shortcut in Emotion-Oriented Image Generation

Guoli Jia, Junyao Hu, Xinwei Long +5

Image generation based on diffusion models has demonstrated impressive capability, motivating exploration into diverse and specialized applications. Owing to the importance of emot…

cs.CV2025

Flow Diverse and Efficient: Learning Momentum Flow Matching via Stochastic Velocity Field Sampling

Zhiyuan Ma, Ruixun Liu, Sixian Liu +2

Recently, the rectified flow (RF) has emerged as the new state-of-the-art among flow-based diffusion models due to its high efficiency advantage in straight path sampling, especial…

cs.CV2025

Context-Aware Autoregressive Models for Multi-Conditional Image Generation

Yixiao Chen, Zhiyuan Ma, Guoli Jia +3

Autoregressive transformers have recently shown impressive image generation quality and efficiency on par with state-of-the-art diffusion models. Unlike diffusion architectures, au…

cs.CV2025

Retrieval-Augmented Visual Question Answering via Built-in Autoregressive Search Engines

Xinwei Long, Zhiyuan Ma, Ermo Hua +3

Retrieval-augmented generation (RAG) has emerged to address the knowledge-intensive visual question answering (VQA) task. Current methods mainly employ separate retrieval and gener…

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