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Hao Liang

7 papers hereh-index 211 citations8 works total

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

author position
  • first author1
  • middle author5

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.CL1
  • cs.LG1
  • cs.MM1
same name
  • Hao Liang — 31 papers, h 12
  • Hao Liang — 12 papers, h 4
  • Hao Liang — 11 papers, h 3
  • Hao Liang — 10 papers, h 7
  • Hao Liang — 6 papers, h 5
  • Hao Liang — 5 papers, h 4

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
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Scone: Bridging Composition and Distinction in Subject-Driven Image Generation via Unified Understanding-Generation Modeling

Yuran Wang, Bohan Zeng, Chengzhuo Tong +6

Subject-driven image generation has advanced from single- to multi-subject composition, while neglecting distinction, the ability to distinguish and generate the correct subject wh…

cs.CV2026

Uni-Synergy: Bridging Understanding and Generation for Personalized Reasoning via Co-operative Reinforcement Learning

Zijun Shen, Sihan Yang, Ruichuan An +5

Unified Multimodal Models (UMMs) excel in general tasks but struggle to bridge the gap between personalized understanding and generation. Prior works largely rely on implicit token…

cs.CV2026

TraceAV-Bench: Benchmarking Multi-Hop Trajectory Reasoning over Long Audio-Visual Videos

Hengyi Feng, Hao Liang, Mingrui Chen +6

Real-world audio-visual understanding requires chaining evidence that is sparse, temporally dispersed, and split across the visual and auditory streams, whereas existing benchmarks…

cs.CV2025

VCU-Bridge: Hierarchical Visual Connotation Understanding via Semantic Bridging

Ming Zhong, Yuanlei Wang, Liuzhou Zhang +7

While Multimodal Large Language Models (MLLMs) excel on benchmarks, their processing paradigm differs from the human ability to integrate visual information. Unlike humans who natu…

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