Improving Label Noise Robustness with Data Augmentation and Semi-Supervised Learning (Student Abstract). - Kento Nishi; Yi Ding 010; Alex Rich 001; Tobias Höllerer (AAAI, 2021)

Augmentation Strategies for Learning With Noisy Labels. - Kento Nishi; Yi Ding 010; Alex Rich 001; Tobias Höllerer (CVPR, 2021)

Joint-Task Regularization for Partially Labeled Multi-Task Learning. - Kento Nishi; Junsik Kim 001; Wanhua Li 001; Hanspeter Pfister (CVPR, 2024)

Towards an Understanding of Stepwise Inference in Transformers: A Synthetic Graph Navigation Model. - Mikail Khona; Maya Okawa; Jan Hula; Rahul Ramesh; Kento Nishi; Robert P. Dick; Ekdeep Singh Lubana; Hidenori Tanaka (ICML, 2024)

Representation Shattering in Transformers: A Synthetic Study with Knowledge Editing. - Kento Nishi; Maya Okawa; Rahul Ramesh; Mikail Khona; Ekdeep Singh Lubana; Hidenori Tanaka (CoRR, 2024)

ICLR: In-Context Learning of Representations. - Core Francisco Park; Andrew Lee 001; Ekdeep Singh Lubana; Yongyi Yang; Maya Okawa; Kento Nishi; Martin Wattenberg; Hidenori Tanaka (ICLR, 2025)