Yuhang Liu
Scholar

Yuhang Liu

Google Scholar ID: 5xZspvQAAAAJ
The University of Adelaide
Representation LearningLLMsLatent Variable ModelsResponsible AI
Citations & Impact
All-time
Citations
443
 
H-index
11
 
i10-index
13
 
Publications
20
 
Co-authors
0
 
Contact
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Resume (English only)
Academic Achievements
  • Multiple papers accepted at top-tier venues including NeurIPS 2025 (2 papers), ICCV 2025, ICLR 2025 (2 papers), TMLR (multiple), ECCV 2024, PR 2024, etc.
  • Nominated as Area Chair for ICLR 2026 by Program Chairs (Aug 2025)
  • Guest Editor for the Entropy Special Issue “Rethinking Representation Learning in the Age of Large Models” (2025)
  • Prolific contributions in causal inference, domain adaptation, representation learning, interpretability of LLMs, and multimodal learning
  • Key focus on identifiability of latent causal models, data diversity, and representation alignment
Background
  • Research Fellow at the Australian Institute for Machine Learning (AIML), The University of Adelaide
  • Collaborating with Prof. Qinfeng (Javen) Shi
  • Research mission: Building Kant’s Bridge through the lens of data diversity
  • Core question: How to align machine-learned representations with the underlying knowledge of data, analogous to the philosophical distinction between appearance and essence
  • Short-term objectives: Enhancing interpretability, controllability, and reasoning in large language models; exploring text diversity to uncover latent patterns in unstructured data; developing foundational theories linking latent variable models and representation learning via data diversity
Co-authors
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Co-authors: 0 (list not available)