EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations | Paper Citation Record

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Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models cites this paper.

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 20

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Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models cites this paper.

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Music102: An $D_{12}$-equivariant transformer for chord progression accompaniment cites this paper.

Music102: An $D_{12}$-equivariant transformer for chord progression accompaniment EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 17

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CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties cites this paper.

CHIPS-FF: Evaluating Universal Machine Learning Force Fields for Material Properties EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Machine Learning Accelerated Descriptor Design for Catalyst Discovery in CO$_2$ to Methanol Conversion cites this paper.

Machine Learning Accelerated Descriptor Design for Catalyst Discovery in CO$_2$ to Methanol Conversion EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 42

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BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps cites this paper.

BoostMD: Accelerating molecular sampling by leveraging ML force field features from previous time-steps EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Learning the Electronic Hamiltonian of Large Atomic Structures cites this paper.

Learning the Electronic Hamiltonian of Large Atomic Structures EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity cites this paper.

Efficient and Scalable Density Functional Theory Hamiltonian Prediction through Adaptive Sparsity EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Transformers trained on proteins can learn to attend to Euclidean distance cites this paper.

Transformers trained on proteins can learn to attend to Euclidean distance EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys cites this paper.

Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 28

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Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity cites this paper.

Global Universal Scaling and Ultra-Small Parameterization in Machine Learning Interatomic Potentials with Super-Linearity EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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The Augmented Potential Method: Multiscale Modeling Toward a Spectral Defect Genome cites this paper.

The Augmented Potential Method: Multiscale Modeling Toward a Spectral Defect Genome EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles cites this paper.

Uncertainty Quantification in Graph Neural Networks with Shallow Ensembles EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Towards Faster and More Compact Foundation Models for Molecular Property Prediction cites this paper.

Towards Faster and More Compact Foundation Models for Molecular Property Prediction EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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LAMBench: A Benchmark for Large Atomistic Models cites this paper.

LAMBench: A Benchmark for Large Atomistic Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Egret-1: Pretrained Neural Network Potentials for Efficient and Accurate Bioorganic Simulation cites this paper.

Egret-1: Pretrained Neural Network Potentials for Efficient and Accurate Bioorganic Simulation EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 119

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Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding cites this paper.

Understanding the Capabilities of Molecular Graph Neural Networks in Materials Science Through Multimodal Learning and Physical Context Encoding EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use cites this paper.

AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework cites this paper.

Beyond Atomic Geometry Representations in Materials Science: A Human-in-the-Loop Multimodal Framework EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Distillation of atomistic foundation models across architectures and chemical domains cites this paper.

Distillation of atomistic foundation models across architectures and chemical domains EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning cites this paper.

Stress-Testing Multimodal Foundation Models for Crystallographic Reasoning EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning cites this paper.

CLOUD: A Scalable and Physics-Informed Foundation Model for Crystal Representation Learning EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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A Scalable and Quantum-Accurate Foundation Model for Biomolecular Force Field via Linearly Tensorized Quadrangle Attention cites this paper.

A Scalable and Quantum-Accurate Foundation Model for Biomolecular Force Field via Linearly Tensorized Quadrangle Attention EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction cites this paper.

Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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OrbitAll: A Unified Quantum Mechanical Representation Deep Learning Framework for All Molecular Systems cites this paper.

OrbitAll: A Unified Quantum Mechanical Representation Deep Learning Framework for All Molecular Systems EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow cites this paper.

Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling cites this paper.

MOFSimBench: Evaluating Universal Machine Learning Interatomic Potentials In Metal--Organic Framework Molecular Modeling EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Equivariant Volumetric Grasping cites this paper.

Equivariant Volumetric Grasping EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 32

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Heterogeneous Ensemble Enables a Universal Uncertainty Metric for Atomistic Foundation Models cites this paper.

Heterogeneous Ensemble Enables a Universal Uncertainty Metric for Atomistic Foundation Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations cites this paper.

Insights into CO dimerization at electrified Cu interfaces from large-scale machine learning simulations EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing cites this paper.

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Platonic Transformers: A Solid Choice For Equivariance cites this paper.

Platonic Transformers: A Solid Choice For Equivariance EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers cites this paper.

OmniMol: Transferring Particle Physics Knowledge to Molecular Dynamics with Point-Edge Transformers EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Pushing the limits of unconstrained machine-learned interatomic potentials cites this paper.

Pushing the limits of unconstrained machine-learned interatomic potentials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory cites this paper.

E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink cites this paper.

Global Plane Waves From Local Gaussians: Periodic Charge Densities in a Blink EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures cites this paper.

From Evaluation to Design: Using Potential Energy Surface Smoothness Metrics to Guide Machine Learning Interatomic Potential Architectures EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces cites this paper.

Faster Molecular Dynamics with Neural Network Potentials via Distilled Multiple Time-Stepping and Non-Conservative Forces EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems cites this paper.

UBio-MolFM: A Universal Molecular Foundation Model for Bio-Systems EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Suiren-1.0 Technical Report: A Family of Molecular Foundation Models cites this paper.

Suiren-1.0 Technical Report: A Family of Molecular Foundation Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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A Priori Sampling of Transition States with Guided Diffusion cites this paper.

A Priori Sampling of Transition States with Guided Diffusion EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 88

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Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys cites this paper.

Benchmarking Chemically Scalable Machine-Learning Interatomic Potentials for Large-Scale Simulations of Multicomponent Alloys EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Knowing when to trust machine-learned interatomic potentials cites this paper.

Knowing when to trust machine-learned interatomic potentials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Selectivity- and Activity-Aware Catalyst Descriptors for CO$_2$ Hydrogenation on Alloy Nanocatalysts using Machine-Learned Force Fields cites this paper.

Selectivity- and Activity-Aware Catalyst Descriptors for CO$_2$ Hydrogenation on Alloy Nanocatalysts using Machine-Learned Force Fields EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials cites this paper.

Benchmarking Compositional Generalisation for Machine Learning Interatomic Potentials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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TSAgent: An Agentic Workflow for Autonomous Transition State Search cites this paper.

TSAgent: An Agentic Workflow for Autonomous Transition State Search EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks cites this paper.

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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Bridging Atomistic Simulation and Experimental Processing Timescales with Goal-Directed Deep Reinforcement Learning cites this paper.

Bridging Atomistic Simulation and Experimental Processing Timescales with Goal-Directed Deep Reinforcement Learning EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials cites this paper.

CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

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CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials cites this paper.

CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 14

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CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials cites this paper.

CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T19:55:01.700374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 09161d06-f1b7-47d2-abdc-3975a6ac0cad · inbound

TriSearch: Learning to Optimize Triangulations via Bistellar Flips cites this paper.

TriSearch: Learning to Optimize Triangulations via Bistellar Flips EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-06-29T08:53:15.580601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2d6d1ab9-3d48-4cab-bdaa-723a1d8ba144 · inbound

DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution cites this paper.

DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 199

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T01:26:24.153026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0b24d30-f6a5-4c24-937d-5e2d36226bd4 · inbound

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning cites this paper.

EpiFormer: Learning Antigen-Antibody Interactions for Epitope Prediction via Geometric Deep Learning EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 218

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T07:06:44.082509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b2efab7c-fb61-4305-96ce-945cef860a2d · inbound

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 144

Resolution: verified exact; arxiv_id, observed 2026-07-02T19:37:19.210749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 3bcb4898-3356-4850-8dbf-f62513a986f1 · inbound

Toward Controllable Catalyst Inverse Design via Large-Scale Autoregressive Pretraining cites this paper.

Toward Controllable Catalyst Inverse Design via Large-Scale Autoregressive Pretraining EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-07-03T19:28:52.430438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0348da0-44fd-4fc5-a458-ba3cc9f5a1b2 · inbound

REViT: Roto-reflection Equivariant Convolutional Vision Transformer cites this paper.

REViT: Roto-reflection Equivariant Convolutional Vision Transformer EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T19:20:07.031409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dd8ce13c-6d75-4539-a4ba-b6b8884f442b · inbound

High-order tensor neural network for iteration-free structure relaxation cites this paper.

High-order tensor neural network for iteration-free structure relaxation EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T04:04:17.683847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f6ea4fd2-9def-4160-a3b0-de2ce7078e18 · inbound

Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles cites this paper.

Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 46

Resolution: unresolved; no resolver link, observed 2026-07-12T02:31:03.871783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7373fbbb-4f75-4f3f-9f90-2f192f98a1d8 · inbound

E3DGS: Unified Geometric-Photometric Equivariance for 3D Gaussian Splatting via Color-as-Geometry Embedding cites this paper.

E3DGS: Unified Geometric-Photometric Equivariance for 3D Gaussian Splatting via Color-as-Geometry Embedding EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-01T23:11:20.579175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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