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Equivariance Is Not All You Need: Characterizing the Utility of Equivariant Graph Neural Networks for Particle Physics Tasks., and . CoRR, (2023)Equivariant Graph Neural Networks for Charged Particle Tracking., , and . CoRR, (2023)Graph Structure from Point Clouds: Geometric Attention is All You Need.. CoRR, (2023)Graph Neural Networks in Particle Physics: Implementations, Innovations, and Challenges., , , , , , , , , and . CoRR, (2022)Symmetry Group Equivariant Architectures for Physics., , , , , , , , , and 1 other author(s). CoRR, (2022)Semi-Equivariant GNN Architectures for Jet Tagging., , and . CoRR, (2022)Benchmarking GPU and TPU Performance with Graph Neural Networks., , , , , and . CoRR, (2022)Track Seeding and Labelling with Embedded-space Graph Neural Networks., , , , , , , , , and 9 other author(s). CoRR, (2020)Physics and Computing Performance of the Exa.TrkX TrackML Pipeline., , , , , , , , , and 14 other author(s). CoRR, (2021)A Language Model for Particle Tracking., , , , , , and . CoRR, (2024)