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cs.LG2025
Force Matching with Relativistic Constraints: A Physics-Inspired Approach to Stable and Efficient Generative Modeling
Yang Cao, Bo Chen, Xiaoyu Li +5
This paper introduces Force Matching (ForM), a novel framework for generative modeling that represents an initial exploration into leveraging special relativistic mechanics to enha…
cs.LG2024
Theoretical Constraints on the Expressive Power of -based Tensor Attention Transformers
Xiaoyu Li, Yingyu Liang, Zhenmei Shi +2
Tensor Attention extends traditional attention mechanisms by capturing high-order correlations across multiple modalities, addressing the limitations of classical matrix-based atte…