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Aoxue Li

11 papers hereh-index 10565 citations18 works total

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

author position
  • first author1
  • middle author9

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.CV11
same name
  • Aoxue Li — 10 papers, h 16
  • Aoxue Li — 1 paper
  • Aoxue Li — 1 paper, h 9
  • Aoxue Li — 1 paper, 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

activity
20232025
most citedGenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing

4 citations · 9 across the 9 of their papers we have counts for

collaborators
Showing 2025 · cs.CVShow all

4 papers · 2 filters

cs.CV2025

SRUM: Fine-Grained Self-Rewarding for Unified Multimodal Models

Weiyang Jin, Yuwei Niu, Jiaqi Liao +4

Recently, remarkable progress has been made in Unified Multimodal Models (UMMs), which integrate vision-language generation and understanding capabilities within a single framework…

cs.CV2025

FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities

Jin Wang, Yao Lai, Aoxue Li +6

The rapid progress of large language models (LLMs) has catalyzed the emergence of multimodal large language models (MLLMs) that unify visual understanding and image generation with…

cs.CV2025

Video-XL-Pro: Reconstructive Token Compression for Extremely Long Video Understanding

Xiangrui Liu, Yan Shu, Zheng Liu +3

Despite advanced token compression techniques, existing multimodal large language models (MLLMs) still struggle with hour-long video understanding. In this work, we propose Video-X…

cs.CV2025

Turbo2K: Towards Ultra-Efficient and High-Quality 2K Video Synthesis

Jingjing Ren, Wenbo Li, Zhongdao Wang +9

Demand for 2K video synthesis is rising with increasing consumer expectations for ultra-clear visuals. While diffusion transformers (DiTs) have demonstrated remarkable capabilities…

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