arXiv Machine Learning June 16, 2026 By Hoa La, Ahan Gupta, Alex Morehead, Jianlin Cheng, Minjia Zhang

MegaFold: Efficient Training of Next-Generation 3D Attention Protein Models on Cross-Platform GPUs

Read the original on arXiv Machine Learning →

arXiv:2506. 20686v2 Announce Type: replace-cross Abstract: Recent advances in biomolecular modeling have been catalyzed by models such as AlphaFold3 (AF3), which introduce science-informed changes to the transformer architecture.

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arXiv AI

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MegaSlide-DiT: Memory-Centric Adaptation and Deformable Local Attention for Efficient Video Diffusion

arXiv:2607. 22696v1 Announce Type: cross Abstract: High-resolution video diffusion models built on Diffusion Transformers (DiTs) deliver strong fidelity but quickly exhaust the memory budget of a single workstation.

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arXiv AI

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arXiv AI

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By Jakub {\L}ucki, Jonathan Becktor, Georgios Georgakis, Rob Royce, Shehryar Khattak

computer-vision robotics efficiency

arXiv AI

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E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory

arXiv:2601. 16622v2 Announce Type: replace-cross Abstract: Equivariant Graph Neural Networks (EGNNs) have become a widely used approach for modeling 3D atomistic systems.

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llms efficiency

arXiv Machine Learning

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arXiv AI

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HIERA: Workload-Aware Planning Across Implementation Spaces for GPU Kernel Optimization

arXiv:2608.21157v1 Announce Type: cross Abstract: High-performance GPU kernels underpin modern deep learning and scientific computing. As workloads become increasingly diverse and GPU hardware evolve...

By Jinghao Wang, Qiqi Gu, Chenpeng Wu, Jianguo Yao, Haibing Guan, Xijun Li

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