Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling.
Yang Cao|Bo Chen|Xiaoyu Li|Yingyu Liang|Zhizhou Sha|Zhenmei Shi|Zhao Song|Mingda Wan
| Anthology ID: | DBLP:conf/cikm/0020CLLSS0W25 |
|---|---|
| Volume: | Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025 |
| Year: | 2025 |
| Venue: | International Conference on Information and Knowledge Management (CIKM) |
| Publisher: | ACM |
| Pages: | 179-188 |
| URL: | https://doi.org/10.1145/3746252.3761227 |
| DOI: | https://doi.org/10.1145/3746252.3761227 |
| DBLP: | conf/cikm/0020CLLSS0W25 |
| BibTeX: |
@inproceedings{cao-2025-force,
author = {Yang Cao and
Bo Chen and
Xiaoyu Li and
Yingyu Liang and
Zhizhou Sha and
Zhenmei Shi and
Zhao Song and
Mingda Wan},
editor = {Meeyoung Cha and
Carl Yang and
Senjuti Basu Roy and
Chanyoung Park and
Zhenhui Jessie Li and
Noseong Park and
Carl Yang and
Senjuti Basu Roy and
Zhenhui Jessie Li and
Jaap Kamps and
Kijung Shin and
Bryan Hooi and
Lifang He},
title = {{Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling}},
booktitle = {{Proceedings of the 34th ACM International Conference on Information and Knowledge Management, CIKM 2025, Seoul, Republic of Korea, November 10-14, 2025}},
pages = {179--188},
publisher = {ACM},
year = {2025},
url = {https://doi.org/10.1145/3746252.3761227},
doi = {https://doi.org/10.1145/3746252.3761227}
}