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} }