Unverified50% confidenceFactExact time
Learned rotation methods (such as SpinQuant and DartQuant) require repeated iterative optimization of the rotation matrix before quantization, resulting in high memory usage and long runtime.
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10/15/2026
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UnverifiedExisting orthogonal transform methods fall roughly into two categories: data-independent fixed transforms (such as the Hadamard rotation) and rotation matrices learned during the calibration stage (such as SpinQuant and DartQuant).79% similarUnverifiedSpinQuant通过Cayley优化在正交矩阵空间中搜索最优旋转，使用少量校准数据微调旋转矩阵，以获得比固定哈达玛矩阵更好的量化效果73% similarUnverifiedQuaRot采用固定的哈达玛矩阵作为旋转矩阵，无需额外训练即可应用，通过将旋转吸收到相邻权重矩阵中而不改变模型输出68% similarUnverifiedMost dynamic 3D methods attempt to align the first and last frames in a post-training processing stage to achieve looping, whereas OuroWorld embeds periodicity directly into the mathematical form of the deformation field, guaranteeing looping holds from the source.64% similarUnverifiedSymplectic integrators embed symplectic geometric structure into time-stepping to ensure phase-space volume is preserved; equivariant neural networks use group-theoretic constraints to make models naturally satisfy symmetries such as rotation and translation.64% similar
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