- Chen, X., Liu, J., Wang, Y., Wang, P., Brand, M., Wang, G., Koike-Akino, T., "SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules", arXiv, March 2024.
BibTeX arXiv- @article{Chen2024mar,
- author = {Chen, Xiangyu and Liu, Jing and Wang, Ye and Wang, Pu and Brand, Matthew and Wang, Guanghui and Koike-Akino, Toshiaki},
- title = {{SuperLoRA: Parameter-Efficient Unified Adaptation of Multi-Layer Attention Modules}},
- journal = {arXiv},
- year = 2024,
- month = mar,
- url = {https://arxiv.org/abs/2403.11887}
- }
- Lowy, A., Li, Z., Liu, J., Koike-Akino, T., Parsons, K., Wang, Y., "Why Does Differential Privacy with Large ε Defend Against Practical Membership Inference Attacks?", AAAI Workshop on Privacy-Preserving Artificial Intelligence, February 2024.
BibTeX TR2024-009 PDF- @inproceedings{Lowy2024feb2,
- author = {Lowy, Andrew and Li, Zhuohang and Liu, Jing and Koike-Akino, Toshiaki and Parsons, Kieran and Wang, Ye},
- title = {{Why Does Differential Privacy with Large ε Defend Against Practical Membership Inference Attacks?}},
- booktitle = {AAAI Workshop on Privacy-Preserving Artificial Intelligence},
- year = 2024,
- month = feb,
- url = {https://www.merl.com/publications/TR2024-009}
- }
- Liu, J., Koike-Akino, T., Wang, P., Brand, M., Wang, Y., Parsons, K., "LoDA: Low-Dimensional Adaptation of Large Language Models", Advances in Neural Information Processing Systems (NeurIPS) workshop, December 2023.
BibTeX TR2023-150 PDF- @inproceedings{Liu2023dec,
- author = {Liu, Jing and Koike-Akino, Toshiaki and Wang, Pu and Brand, Matthew and Wang, Ye and Parsons, Kieran},
- title = {{LoDA: Low-Dimensional Adaptation of Large Language Models}},
- booktitle = {Advances in Neural Information Processing Systems (NeurIPS) workshop},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-150}
- }
- Li, Z., Lowy, A., Liu, J., Koike-Akino, T., Malin, B., Parsons, K., Wang, Y., "Exploring User-level Gradient Inversion with a Diffusion Prior", International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS, December 2023.
BibTeX TR2023-149 PDF- @inproceedings{Li2023dec,
- author = {Li, Zhuohang and Lowy, Andrew and Liu, Jing and Koike-Akino, Toshiaki and Malin, Bradley and Parsons, Kieran and Wang, Ye},
- title = {{Exploring User-level Gradient Inversion with a Diffusion Prior}},
- booktitle = {International Workshop on Federated Learning in the Age of Foundation Models in Conjunction with NeurIPS},
- year = 2023,
- month = dec,
- url = {https://www.merl.com/publications/TR2023-149}
- }