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Chao Huang

5 papers hereh-index 3198 citations7 works total

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

author position
  • last author5

Across the 5 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CV2
  • cs.IR2
  • cs.LG1
same name
  • Chao Huang — 20 papers, h 11
  • Chao Huang — 8 papers, h 8
  • Chao Huang — 8 papers, h 6
  • Chao Huang — 6 papers, h 1
  • Chao Huang — 6 papers, h 3
  • Chao Huang — 6 papers, h 5

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

collaborators

5 papers

cs.CV2026

VideoAgent: All-in-One Framework for Video Understanding and Editing

Hengji Zhou, Lingxuan Huang, Jian Wang +4

Video editing has become essential in digital media creation, yet existing automated systems are restricted to short segment processing and domain-specific tasks. They face two cri…

cs.CV2026

ViMax: Agentic Video Generation

Lingxuan Huang, Sizhe He, Hengji Zhou +3

Long-form video generation requires systematic narrative planning and visual consistency that current short-clip methods cannot provide. Existing methods generate isolated sequence…

cs.IR2025

Pre-training for Recommendation Unlearning

Guoxuan Chen, Lianghao Xia, Chao Huang

Modern recommender systems powered by Graph Neural Networks (GNNs) excel at modeling complex user-item interactions, yet increasingly face scenarios requiring selective forgetting…

cs.IR2025

LightGNN: Simple Graph Neural Network for Recommendation

Guoxuan Chen, Lianghao Xia, Chao Huang

Graph neural networks (GNNs) have demonstrated superior performance in collaborative recommendation through their ability to conduct high-order representation smoothing, effectivel…

cs.LG2025

DiffGraph: Heterogeneous Graph Diffusion Model

Zongwei Li, Lianghao Xia, Hua Hua +3

Recent advances in Graph Neural Networks (GNNs) have revolutionized graph-structured data modeling, yet traditional GNNs struggle with complex heterogeneous structures prevalent in…

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