Ruiqing Sun, Sen Yang, Dawei Feng, Bo Ding, Yijie Wang, Huaimin Wang: TreeRef-BFN: Equivariance-Free De Novo Molecule Generation based on 2D Topology and Internal 3D Geometry https://arxiv.org/abs/2609.32502 https://arxiv.org/pdf/2609.32502 https://arxiv.org/html/2609.32502
September 29, 2026 at 6:40 AM
Ruiqing Sun, Sen Yang, Dawei Feng, Bo Ding, Yijie Wang, Huaimin Wang: TreeRef-BFN: Equivariance-Free De Novo Molecule Generation based on 2D Topology and Internal 3D Geometry https://arxiv.org/abs/2609.32502 https://arxiv.org/pdf/2609.32502 https://arxiv.org/html/2609.32502
Sarra Amiri, Nelly Pustelnik, Jean-Christophe Pesquet: EQUIVARIANCE VERSUS FIRM NON-EXPANSIVENESS IN INCREMENTAL PROXIMAL GRADIENT METHODS FOR PLUG-AND-PLAY DENOISING https://hal.science/hal-05765924v1 [info.info-ts]
September 29, 2026 at 3:00 AM
Sarra Amiri, Nelly Pustelnik, Jean-Christophe Pesquet: EQUIVARIANCE VERSUS FIRM NON-EXPANSIVENESS IN INCREMENTAL PROXIMAL GRADIENT METHODS FOR PLUG-AND-PLAY DENOISING https://hal.science/hal-05765924v1 [info.info-ts]
Soumic Sarkar: Noise Stability and Rotational Equivariance of Image-Induced Hamiltonian Spectra for Robust Unsupervised Segmentation https://arxiv.org/abs/2609.30280 https://arxiv.org/pdf/2609.30280 https://arxiv.org/html/2609.30280
September 28, 2026 at 6:45 AM
Soumic Sarkar: Noise Stability and Rotational Equivariance of Image-Induced Hamiltonian Spectra for Robust Unsupervised Segmentation https://arxiv.org/abs/2609.30280 https://arxiv.org/pdf/2609.30280 https://arxiv.org/html/2609.30280
New preprint is out: "Fundamental Limits of Transferability and Equivariance in Algebraic Signal Models I: Finite Dimensions"
zenodo.org/records/2297...
zenodo.org/records/2297...
Fundamental Limits of Transferability and Equivariance in Algebraic Signal Models I: Finite Dimensions
We study the fundamental limits of transferability inalgebraic signal processing through homomorphisms between algebraic signalmodels. Homomorphisms are linear maps between the signal spaces of twomod...
zenodo.org
September 26, 2026 at 4:52 PM
New preprint is out: "Fundamental Limits of Transferability and Equivariance in Algebraic Signal Models I: Finite Dimensions"
zenodo.org/records/2297...
zenodo.org/records/2297...
Ho Jang, Sankha Subhra Bakshi, Gia-Wei Chern: Exact Equivariance from Ordinary Neural Networks for Lattice Many-Body Dynamics https://arxiv.org/abs/2609.27132 https://arxiv.org/pdf/2609.27132 https://arxiv.org/html/2609.27132
September 24, 2026 at 6:53 AM
Ho Jang, Sankha Subhra Bakshi, Gia-Wei Chern: Exact Equivariance from Ordinary Neural Networks for Lattice Many-Body Dynamics https://arxiv.org/abs/2609.27132 https://arxiv.org/pdf/2609.27132 https://arxiv.org/html/2609.27132
Zhengyang Zhang, Haojin Zhou: The Equivariance Criterion in a Linear Model for Random-$X$ Cases https://arxiv.org/abs/2609.16897 https://arxiv.org/pdf/2609.16897 https://arxiv.org/html/2609.16897
September 16, 2026 at 6:51 AM
Zhengyang Zhang, Haojin Zhou: The Equivariance Criterion in a Linear Model for Random-$X$ Cases https://arxiv.org/abs/2609.16897 https://arxiv.org/pdf/2609.16897 https://arxiv.org/html/2609.16897
Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/abs/2609.10186
arXiv abstract link
arxiv.org
September 11, 2026 at 3:33 AM
Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
David D. Dai, Yen-Ting Lin, Marin Solja\v{c}i\'c: Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance https://arxiv.org/abs/2609.10186 https://arxiv.org/pdf/2609.10186 https://arxiv.org/html/2609.10186
September 10, 2026 at 6:53 AM
David D. Dai, Yen-Ting Lin, Marin Solja\v{c}i\'c: Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance https://arxiv.org/abs/2609.10186 https://arxiv.org/pdf/2609.10186 https://arxiv.org/html/2609.10186
Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/abs/2609.10186
arXiv abstract link
arxiv.org
September 10, 2026 at 4:01 AM
Fast, Accurate, and Scalable Fermionic Neural Networks via Translation Equivariance
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
https://arxiv.org/pdf/2609.10186
David D. Dai, Yen-Ting Lin, Marin Soljačić.
Andrei Manolache, Mathias Niepert: Equivariance Breaks the Learning Rate https://arxiv.org/abs/2609.08381 https://arxiv.org/pdf/2609.08381 https://arxiv.org/html/2609.08381
September 9, 2026 at 6:46 AM
Andrei Manolache, Mathias Niepert: Equivariance Breaks the Learning Rate https://arxiv.org/abs/2609.08381 https://arxiv.org/pdf/2609.08381 https://arxiv.org/html/2609.08381
Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning
Read more: https://arxiv.org/html/2608.28018v1
Read more: https://arxiv.org/html/2608.28018v1
September 4, 2026 at 6:42 PM
Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning
Read more: https://arxiv.org/html/2608.28018v1
Read more: https://arxiv.org/html/2608.28018v1
Jocelyn Nembe
Equivariance, Curvature and Symmetry in Functional Covariance Estimation
https://arxiv.org/abs/2609.03042
Equivariance, Curvature and Symmetry in Functional Covariance Estimation
https://arxiv.org/abs/2609.03042
September 4, 2026 at 4:20 PM
Jocelyn Nembe
Equivariance, Curvature and Symmetry in Functional Covariance Estimation
https://arxiv.org/abs/2609.03042
Equivariance, Curvature and Symmetry in Functional Covariance Estimation
https://arxiv.org/abs/2609.03042
Jocelyn Nembe: Equivariance, Curvature and Symmetry in Functional Covariance Estimation https://arxiv.org/abs/2609.03042 https://arxiv.org/pdf/2609.03042 https://arxiv.org/html/2609.03042
September 4, 2026 at 6:50 AM
Jocelyn Nembe: Equivariance, Curvature and Symmetry in Functional Covariance Estimation https://arxiv.org/abs/2609.03042 https://arxiv.org/pdf/2609.03042 https://arxiv.org/html/2609.03042
Kaizhen Tan, Yang Feng, Heqing Du, Siru Tao, Xin Xu, Hanzhe Hong: Teaching Vision-Language Models to Use the Scale They Are Given: Label-Free Equivariance Training for Metric Physical Reasoning https://arxiv.org/abs/2609.00658 https://arxiv.org/pdf/2609.00658 https://arxiv.org/html/2609.00658
September 2, 2026 at 6:40 AM
Kaizhen Tan, Yang Feng, Heqing Du, Siru Tao, Xin Xu, Hanzhe Hong: Teaching Vision-Language Models to Use the Scale They Are Given: Label-Free Equivariance Training for Metric Physical Reasoning https://arxiv.org/abs/2609.00658 https://arxiv.org/pdf/2609.00658 https://arxiv.org/html/2609.00658
Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance
Kenny Schlegel et al.
#arXiv #cs.AI
Kenny Schlegel et al.
#arXiv #cs.AI
Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance
Encoding temporal order is a fundamental requirement for sequence representations in Hyperdimensional Computing. Fractional Power Encoding provides similarity-preserving position vectors whose inner products approximate shift-invariant kernels, and it supports shift-equivariant transformations of e…
arxiv.org
September 1, 2026 at 3:33 PM
Peter Lippmann, Fred A. Hamprecht: Rotational Equivariance in Machine Learning: A Comprehensive Tutorial https://arxiv.org/abs/2608.31045 https://arxiv.org/pdf/2608.31045 https://arxiv.org/html/2608.31045
September 1, 2026 at 6:45 AM
Peter Lippmann, Fred A. Hamprecht: Rotational Equivariance in Machine Learning: A Comprehensive Tutorial https://arxiv.org/abs/2608.31045 https://arxiv.org/pdf/2608.31045 https://arxiv.org/html/2608.31045
Schlegel, Rachkovskij, Kleyko, Loutfi, Streif, Osipov: Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance https://arxiv.org/abs/2608.28334 https://arxiv.org/pdf/2608.28334 https://arxiv.org/html/2608.28334
September 1, 2026 at 6:39 AM
Schlegel, Rachkovskij, Kleyko, Loutfi, Streif, Osipov: Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance https://arxiv.org/abs/2608.28334 https://arxiv.org/pdf/2608.28334 https://arxiv.org/html/2608.28334
The Twin Worlds framework enhances reliability in knowledge-intensive reasoning through equivariance-based abstention, helping models recognize insufficient evidence and avoid unsupported answers, outperforming existing methods and mitigating misinformation risk. https://arxiv.org/abs/2608.28018
Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning
ArXiv link for Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning
arxiv.org
August 31, 2026 at 5:10 PM
The Twin Worlds framework enhances reliability in knowledge-intensive reasoning through equivariance-based abstention, helping models recognize insufficient evidence and avoid unsupported answers, outperforming existing methods and mitigating misinformation risk. https://arxiv.org/abs/2608.28018
Vy Nguyen, Ziqi Xu, Jeffrey Chan, Estrid He, Feng Xia, Renqiang Luo, Erik Cambria, Xiuzhen Zhang: Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning https://arxiv.org/abs/2608.28018 https://arxiv.org/pdf/2608.28018 https://arxiv.org/html/2608.28018
August 31, 2026 at 6:40 AM
Vy Nguyen, Ziqi Xu, Jeffrey Chan, Estrid He, Feng Xia, Renqiang Luo, Erik Cambria, Xiuzhen Zhang: Twin Worlds: Equivariance-Based Abstention for Evidence-Grounded Reasoning https://arxiv.org/abs/2608.28018 https://arxiv.org/pdf/2608.28018 https://arxiv.org/html/2608.28018
Schlegel, Rachkovskij, Kleyko, Loutfi, Streif, Osipov: Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance https://arxiv.org/abs/2608.28334 https://arxiv.org/pdf/2608.28334 https://arxiv.org/html/2608.28334
August 31, 2026 at 6:40 AM
Schlegel, Rachkovskij, Kleyko, Loutfi, Streif, Osipov: Real-Valued Hyperdimensional Sequence Representations with Hadamard Product Binding and Shift Equivariance https://arxiv.org/abs/2608.28334 https://arxiv.org/pdf/2608.28334 https://arxiv.org/html/2608.28334
New paper shows Adam destroys low-rank implicit regularization in factorized models while GD, Muon and Shampoo preserve it via gauge equivariance. The choice of optimizer isn't just about convergence speed anymore. https://arxiv.org/abs/2608.05136 https://github.com/idevender/loss-basis-adam
August 20, 2026 at 11:49 AM
New paper shows Adam destroys low-rank implicit regularization in factorized models while GD, Muon and Shampoo preserve it via gauge equivariance. The choice of optimizer isn't just about convergence speed anymore. https://arxiv.org/abs/2608.05136 https://github.com/idevender/loss-basis-adam
Yujie Zhang, Chunlei Zhao, Yuzong Lin, Yuxuan Guo, Xiaohui Jia, Jinyue Liu
Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration
https://arxiv.org/abs/2608.15532
Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration
https://arxiv.org/abs/2608.15532
August 18, 2026 at 6:57 PM
Yujie Zhang, Chunlei Zhao, Yuzong Lin, Yuxuan Guo, Xiaohui Jia, Jinyue Liu
Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration
https://arxiv.org/abs/2608.15532
Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration
https://arxiv.org/abs/2608.15532
Yujie Zhang, Chunlei Zhao, Yuzong Lin, Yuxuan Guo, Xiaohui Jia, Jinyue Liu: Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration https://arxiv.org/abs/2608.15532 https://arxiv.org/pdf/2608.15532 https://arxiv.org/html/2608.15532
August 18, 2026 at 6:44 AM
Yujie Zhang, Chunlei Zhao, Yuzong Lin, Yuxuan Guo, Xiaohui Jia, Jinyue Liu: Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration https://arxiv.org/abs/2608.15532 https://arxiv.org/pdf/2608.15532 https://arxiv.org/html/2608.15532
And how CNNs learn to break translation equivariance as the cheri on top ;)
August 12, 2026 at 7:11 PM
And how CNNs learn to break translation equivariance as the cheri on top ;)
But did you mention translation equivariance? That would have changed everything for her!
August 12, 2026 at 6:32 PM
But did you mention translation equivariance? That would have changed everything for her!