- 2024-07: One paper on autonomous driving accepted to ECCV 2024.
- 2024-04: One paper on salient object detection accepted to TGRS 2024.
- 2024-02: Two papers on autonomous driving accepted to CVPR 2024.
- 2024-01: One paper on explainable deep networks accepted to ICLR 2024.
- 2023-01: One paper on explainable deep networks accepted to ICLR 2023.
- 2022-07: One paper on dynamic metric learning accepted to ECCV 2022.
- 2022-03: One paper on explainable metric learning accepted to CVPR 2022.
- 2021-07: One paper on deep metric learning accepted to ICCV 2021.
Preprints:
- Preventing Local Pitfalls in Vector Quantization via Optimal Transport
- Exploring Unified Perspective For Fast Shapley Value Estimation
Selected publications:
- Path Choice Matters for Clear Attribution in Path Methods
- Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint
Research Experience
During his Ph.D., he mainly focused on research in explainable AI, neural network theory, and large multimodal models.
Education
Earned BE degree from the Department of Automation and a second BA degree from the School of Economics and Management at Tsinghua University in 2021.
Background
Research interests span across computer vision and deep learning theory. Specifically, explainable AI (black-box XAI: axiomatic interpretation, neural visualization; white-box XAI: concept alignment, white-box architecture), neural network theory (optimization: efficient optimization, convergence analysis; inductive bias: frequency bias, piece-wise linear model), and large multimodal models (visual tokenizer, native multimodal model, GUI agent, efficient VLM, safety & alignment). Currently a final-year Ph.D. student in the i-VisionGroup at the Department of Automation, Tsinghua University, under the guidance of Professor Jiwen Lu.
Miscellany
Personal website: https://skylerhallinan.com/. Contact information available through email, Google Scholar, GitHub, Xiaohongshu, etc.