| Fine-grained neural network explanation by identifying input features with predictive information Y Zhang, A Khakzar, Y Li, A Farshad, ST Kim, N Navab Advances in Neural Information Processing Systems (NeurIPS) 2021, 2021 | 33 | 2021 |
| The stronger the diffusion model, the easier the backdoor: Data poisoning to induce copyright breaches without adjusting finetuning pipeline H Wang, Q Shen, Y Tong, Y Zhang, K Kawaguchi International Conference on Machine Learning (ICML) 2024, 2024 | 25 | 2024 |
| Explaining covid-19 and thoracic pathology model predictions by identifying informative input features A Khakzar, Y Zhang, W Mansour, Y Cai, Y Li, Y Zhang, ST Kim, N Navab Medical Image Computing and Computer Assisted Intervention (MICCAI) 2021, 2021 | 18 | 2021 |
| Enhancing Semantic Fidelity in Text-to-Image Synthesis: Attention Regulation in Diffusion Models Y Zhang, TT Tzun, LW Hern, T Sim, K Kawaguchi The European Conference on Computer Vision (ECCV) 2024, 2024 | 10 | 2024 |
| Finercut: Finer-grained interpretable layer pruning for large language models Y Zhang, Y Li, X Wang, Q Shen, B Plank, B Bischl, M Rezaei, ... arXiv preprint arXiv:2405.18218, 2024 | 7 | 2024 |
| Investigating Copyright Issues of Diffusion Models under Practical Scenarios Y Zhang, TT Tzun, LW Hern, H Wang, K Kawaguchi ECCV 2024 Workshop The Dark Side of Generative AIs and Beyond, 2023 | 5* | 2023 |
| Investigating Layer Importance in Large Language Models Y Zhang, Y Dong, K Kawaguchi EMNLP 2024 BlackboxNLP, 2024 | 4 | 2024 |
| Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization Q Shen, Y Wang, Z Yang, X Li, H Wang, Y Zhang, J Scarlett, Z Zhu, ... Advances in Neural Information Processing Systems (NeurIPS) 2024, 2024 | 3 | 2024 |
| AttributionLab: Faithfulness of Feature Attribution Under Controllable Environments Y Zhang, Y Li, H Brown, M Rezaei, B Bischl, P Torr, A Khakzar, ... Neurips 2023 Workshop XAIA, 2023 | 2 | 2023 |
| Analyzing the Effects of Handling Data Imbalance on Learned Features from Medical Images by Looking Into the Models A Khakzar, Y Li, Y Zhang, M Sanisoglu, ST Kim, M Rezaei, B Bischl, ... ICML 2022 Workshop on Interpretable Machine Learning in Healthcare, 2022 | 1 | 2022 |
| Effortless Efficiency: Low-Cost Pruning of Diffusion Models Y Zhang, E Jin, Y Dong, A Khakzar, P Torr, J Stegmaier, K Kawaguchi arXiv preprint arXiv:2412.02852, 2024 | | 2024 |
| A Dual-Perspective Approach to Evaluating Feature Attribution Methods Y Li, Y Zhang, K Kawaguchi, A Khakzar, B Bischl, M Rezaei Transaction on Machine Learning Research, 2023 | | 2023 |
Kenji KawaguchiPresidential Young Professor, National University of Singaporenus.edu.sg의 이메일 확인됨