| 2026 | AAAI | The Strong Lottery Ticket Hypothesis for Multi-Head Attention Mechanisms. | Hikari Otsuka, Daiki Chijiwa, Yasuyuki Okoshi, Daichi Fujiki, Susumu Takeuchi, Masato Motomura |
| 2025 | CVPR | Post-pre-training for Modality Alignment in Vision-Language Foundation Models. | Shin'ya Yamaguchi, Dewei Feng, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa |
| 2025 | ICML | Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models. | Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida, Kuniko Saito, Susumu Takeuchi |
| 2025 | ICML | Plausible Token Amplification for Improving Accuracy of Differentially Private In-Context Learning Based on Implicit Bayesian Inference. | Yusuke Yamasaki, Kenta Niwa, Daiki Chijiwa, Takumi Fukami, Takayuki Miura |
| 2024 | ACML | Toward Data Efficient Model Merging between Different Datasets without Performance Degradation. | Masanori Yamada, Tomoya Yamashita, Shin'ya Yamaguchi, Daiki Chijiwa |
| 2024 | CVPR | Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks. | Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa |
| 2024 | ICLR | Transferring Learning Trajectories of Neural Networks. | Daiki Chijiwa |