Yuan-Hong Liao
Toronto, Canada
I’ll be on the job market for an industry role starting early 2025. If my research aligns with your needs, please feel free to reach out via email.
I will be in Miami for EMNLP’24. Drop me an email if you’d like to have a chat or grad a coffee
I am a final-year Ph.D. student at the University of Toronto and Vector Institute. I am fortunate to be supervised by Prof. Sanja Fidler. Previously, I was an CV/ML scientist intern at NVIDIA Toronto AI lab in 2022 - 2023 and Amazon Astros team in 2024.
I am interested in developing and analyzing large Vision-Language Models. Specifically, I focus on the application of building scalable & efficient data labeling pipeline. Check my papers in
- Improving human-annotated labels [CVPR’21] [ICLR’24]
- Improving machine-generated labels [EMNLP’24] [arXiv’24]
Previous experiences
Prior to my Ph.D., I was a visiting student at Vector Institute and USC in 2018 and 2017, respectively. I was fortunate to start by AI research at National Tsing Hua University, supervised by Prof. Min Sun.news
Sep 20, 2024 | Our paper Reasoning Paths with Reference Objects Elicit Quantitative Spatial Reasoning in Large Vision-Language Models is accepted to EMNLP 2024 |
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Jul 22, 2024 | Start my internship at Amazon Astro team at Seattle! |
Apr 09, 2024 | New preprint out on arXiv Can Feedback Enhance Semantic Grounding in Large Vision-Language Models?! |
Jan 15, 2024 | Our paper Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets is accepted to ICLR 2024 |
Oct 01, 2023 | Our paper Bridging the Sim2Real gap with CARE: Supervised Detection Adaptation with Conditional Alignment and Reweighting is accepted to TMLR 2023 |