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Tongliang Liu

15 papers hereh-index 7131 citations19 works total

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

author position
  • middle author13
  • last author1

Across the 14 of 15 papers where every author was matched, so the position is known.

fields
  • cs.LG9
  • cs.CV4
  • cs.AI1
  • cs.CL1
same name
  • Tongliang Liu — 151 papers, h 76
  • Tongliang Liu — 55 papers, h 21
  • Tongliang Liu — 29 papers, h 8
  • Tongliang Liu — 13 papers, h 6
  • Tongliang Liu — 8 papers, h 6
  • Tongliang Liu — 7 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

activity
20232026
most citedHCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization

3 citations · 7 across the 13 of their papers we have counts for

collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Unsupervised Synthetic Image Attribution: Alignment and Disentanglement

Zongfang Liu, Guangyi Chen, Boyang Sun +2

As the quality of synthetic images improves, identifying the underlying concepts of model-generated images is becoming increasingly crucial for copyright protection and ensuring mo…

cs.CV2026

Mirage2Matter: A Physically Grounded Gaussian World Model from Video

Zhengqing Gao, Ziwen Li, Xin Wang +12

The scalability of embodied intelligence is fundamentally constrained by the scarcity of real-world interaction data. While simulation platforms provide a promising alternative, ex…

cs.CV2024

Improving Accuracy-robustness Trade-off via Pixel Reweighted Adversarial Training

Jiacheng Zhang, Feng Liu, Dawei Zhou +2

Adversarial training (AT) trains models using adversarial examples (AEs), which are natural images modified with specific perturbations to mislead the model. These perturbations ar…

cs.CV2024★ 3 cited

HCVP: Leveraging Hierarchical Contrastive Visual Prompt for Domain Generalization

Guanglin Zhou, Zhongyi Han, Shiming Chen +5

Domain Generalization (DG) endeavors to create machine learning models that excel in unseen scenarios by learning invariant features. In DG, the prevalent practice of constraining…

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