Tokenizing Electron Cloud in Protein-Ligand Interaction Learning | Paper Citation Record

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This paper cites ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning ShEPhERD: Diffusing shape, electrostatics, and pharmacophores for bioisosteric drug design

Reference 1

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This paper cites Gotennet: Rethinking efficient 3d equivariant graph neural networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Gotennet: Rethinking efficient 3d equivariant graph neural networks

Reference 2

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This paper cites Gfn2-xtb-an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Gfn2-xtb-an accurate and broadly parametrized self-consistent tight-binding quantum chemical method with multipole electrostatics and density-dependent dispersion contributions

Reference 3

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 4

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This paper cites Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation

Reference 5

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This paper cites A bird's-eye view of density-functional theory.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning A bird's-eye view of density-functional theory

Reference 6

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This paper cites Are high-degree representations really unnecessary in equivariant graph neural networks? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Are high-degree representations really unnecessary in equivariant graph neural networks? In The Thirty-eighth Annual Conference on Neural Information Processing Systems, 2024

Reference 7

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This paper cites Self-supervised learning with random-projection quantizer for speech recognition.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Self-supervised learning with random-projection quantizer for speech recognition

Reference 8

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This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 9

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This paper cites Insights into protein--ligand interactions: mechanisms, models, and methods.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Insights into protein--ligand interactions: mechanisms, models, and methods

Reference 10

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This paper cites Insights into protein–ligand interactions: Mechanisms, models, and methods.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Insights into protein–ligand interactions: Mechanisms, models, and methods

Reference 11

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This paper cites Taming Transformers for High-Resolution Image Synthesis.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Taming Transformers for High-Resolution Image Synthesis

Reference 12

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This paper cites Friesner, Jay L.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Friesner, Jay L

Reference 13

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This paper cites Fragment and geometry aware tokenization of molecules for structure-based drug design using language models.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Fragment and geometry aware tokenization of molecules for structure-based drug design using language models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:36.198008Z

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This paper cites Insights into the molecular mechanisms of protein-ligand interactions by molecular docking and molecular dynamics simulation: A case of oligopeptide binding protein.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Insights into the molecular mechanisms of protein-ligand interactions by molecular docking and molecular dynamics simulation: A case of oligopeptide binding protein

Reference 15

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Observation 22c5ba8a-e951-4d27-86f8-b491e9e1703d · outbound

This paper cites Directional Message Passing for Molecular Graphs.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Directional Message Passing for Molecular Graphs

Reference 16

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This paper cites GemNet: Universal Directional Graph Neural Networks for Molecules.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning GemNet: Universal Directional Graph Neural Networks for Molecules

Reference 17

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This paper cites e3nn: Euclidean Neural Networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning e3nn: Euclidean Neural Networks

Reference 18

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This paper cites De Novo Molecular Generation via Connection-aware Motif Mining.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning De Novo Molecular Generation via Connection-aware Motif Mining

Reference 19

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This paper cites Schoenholz, Patrick F.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Schoenholz, Patrick F

Reference 20

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This paper cites Grosse-Kunstleve, Nicholas K.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Grosse-Kunstleve, Nicholas K

Reference 21

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This paper cites Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers

Reference 22

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This paper cites Sofroniew, Deniz Oktay, Zeming Lin, Robert Verkuil, Vincent Q.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Sofroniew, Deniz Oktay, Zeming Lin, Robert Verkuil, Vincent Q

Reference 23

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This paper cites Masked Autoencoders Are Scalable Vision Learners.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Masked Autoencoders Are Scalable Vision Learners

Reference 24

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This paper cites Distilling the Knowledge in a Neural Network.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Distilling the Knowledge in a Neural Network

Reference 25

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This paper cites Equivariant diffusion for molecule generation in 3d.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Equivariant diffusion for molecule generation in 3d

Reference 26

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This paper cites Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Straightening out the straight-through estimator: Overcoming optimization challenges in vector quantized networks

Reference 27

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This paper cites Exploring protein--ligand binding affinity prediction with electron density-based geometric deep learning.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Exploring protein--ligand binding affinity prediction with electron density-based geometric deep learning

Reference 28

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This paper cites Junction tree variational autoencoder for molecular graph generation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Junction tree variational autoencoder for molecular graph generation

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.894287Z

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This paper cites Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unsupervised Protein-Ligand Binding Energy Prediction via Neural Euler's Rotation Equation

Reference 30

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This paper cites DSMB ind: an unsupervised generative modeling framework for binding energy prediction.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning DSMB ind: an unsupervised generative modeling framework for binding energy prediction

Reference 31

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This paper cites Generalist equivariant transformer towards 3d molecular interaction learning, 2024.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Generalist equivariant transformer towards 3d molecular interaction learning, 2024

Reference 32

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Neural operator: learning maps between function spaces with applications to pdes

Reference 33

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This paper cites Intermolecular forces in biology.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Intermolecular forces in biology

Reference 34

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This paper cites Autoregressive image generation using residual quantization.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Autoregressive image generation using residual quantization

Reference 35

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This paper cites Geometry Informed Tokenization of Molecules for Language Model Generation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Geometry Informed Tokenization of Molecules for Language Model Generation

Reference 36

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This paper cites Neural Operator: Graph Kernel Network for Partial Differential Equations.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Neural Operator: Graph Kernel Network for Partial Differential Equations

Reference 37

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Multipole graph neural operator for parametric partial differential equations

Reference 38

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Fourier Neural Operator for Parametric Partial Differential Equations

Reference 39

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Equiformer: Equivariant graph attention transformer for 3d atomistic graphs

Reference 40

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Equiformerv2: Improved equivariant transformer for scaling to higher-degree representations

Reference 41

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 43

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 44

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

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This paper cites Pdb-wide collection of binding data: current status of the pdbbind database.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Pdb-wide collection of binding data: current status of the pdbbind database

Reference 46

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Learning nonlinear operators via deeponet based on the universal approximation theorem of operators

Reference 47

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Rotamer density estimator is an unsupervised learner of the effect of mutations on protein-protein interaction

Reference 48

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators

Reference 49

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Prot2token: A multi-task framework for protein language processing using autoregressive language modeling

Reference 50

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This paper cites Revealing non-covalent interactions in molecular crystals through their experimental electron densities.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Revealing non-covalent interactions in molecular crystals through their experimental electron densities

Reference 51

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This paper cites E(n) Equivariant Graph Neural Networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning E(n) Equivariant Graph Neural Networks

Reference 52

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This paper cites Computational complexity of interacting electrons and fundamental limitations of density functional theory.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Computational complexity of interacting electrons and fundamental limitations of density functional theory

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.611848Z

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Observation a5f42a58-6288-44e7-9534-9d5e5755e96c · outbound

This paper cites u tt, P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, and K.-R. M\.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning u tt, P.-J. Kindermans, H. E. Sauceda, S. Chmiela, A. Tkatchenko, and K.-R. M\

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.594671Z

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Observation b4240888-a439-4110-97c9-70cfd99fd410 · outbound

This paper cites Theis, Michael Sattler, and Grzegorz Maria Popowicz.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Theis, Michael Sattler, and Grzegorz Maria Popowicz

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.578845Z

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This paper cites Multi-scale representation learning on proteins.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Multi-scale representation learning on proteins

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.562288Z

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Observation 6a31a185-2144-4316-8c47-0ea85edd0622 · outbound

This paper cites SurfPro: Functional Protein Design Based on Continuous Surface.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning SurfPro: Functional Protein Design Based on Continuous Surface

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.546392Z

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This paper cites a rk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan G \.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning a rk, Dominique Beaini, Gabriele Corso, Prudencio Tossou, Christian Dallago, Stephan G \

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.546691Z

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This paper cites Saprot: Protein language modeling with structure-aware vocabulary.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Saprot: Protein language modeling with structure-aware vocabulary

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.530518Z

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This paper cites Correia, and Michael M.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Correia, and Michael M

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.515245Z

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Equivariant transformers for neural network based molecular potentials

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.499097Z

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 62

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:26:35.483125Z

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Observation aebbdee3-6607-4afb-8851-435630f6d22b · outbound

This paper cites ATOM3D: Tasks On Molecules in Three Dimensions.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning ATOM3D: Tasks On Molecules in Three Dimensions

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.596667Z

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This paper cites Gilchrist, Johannes S \"o ding, and Martin Steinegger.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Gilchrist, Johannes S \"o ding, and Martin Steinegger

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.467146Z

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This paper cites Learning Hierarchical Protein Representations via Complete 3D Graph Networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Learning Hierarchical Protein Representations via Complete 3D Graph Networks

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.606871Z

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This paper cites The pdbbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning The pdbbind database: collection of binding affinities for protein-ligand complexes with known three-dimensional structures

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.450752Z

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This paper cites A new perspective on building efficient and expressive 3d equivariant graph neural networks.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning A new perspective on building efficient and expressive 3d equivariant graph neural networks

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.431258Z

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This paper cites Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Transformers are Deep Infinite-Dimensional Non-Mercer Binary Kernel Machines

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.623795Z

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 69

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 70

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:26:35.397402Z

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-07T14:26:35.379848Z

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Observation 038bb970-ab15-4e5e-8542-59c574b8f439 · outbound

This paper cites Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Learning to Predict Mutation Effects of Protein-Protein Interactions by Microenvironment-aware Hierarchical Prompt Learning

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.645752Z

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Observation 68b0f6f3-f364-42db-9538-464e7e92c117 · outbound

This paper cites GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.651267Z

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Observation ca3c3fb7-b1a6-424d-a639-a3c74b4a94e7 · outbound

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Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Vector-quantized Image Modeling with Improved VQGAN

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.656194Z

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Observation 352e2f82-1c4f-45c1-a2ee-b37bbadc088d · outbound

This paper cites Proteinmae: masked autoencoder for protein surface self-supervised learning.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Proteinmae: masked autoencoder for protein surface self-supervised learning

Reference 75

Resolution: verified exact; doi, observed 2026-08-07T14:26:34.733820Z

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Observation 839bdb76-8ee3-4e76-915d-f8abd6962d15 · outbound

This paper cites Ecloudgen: Access to broader chemical space for structure-based molecule generation.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Ecloudgen: Access to broader chemical space for structure-based molecule generation

Reference 76

Resolution: verified exact; doi, observed 2026-08-07T14:26:34.717534Z

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Observation 16edbb0c-19e3-454d-843f-c5f84bfe4ae0 · outbound

This paper cites Reliable data distillation on graph convolutional network.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Reliable data distillation on graph convolutional network

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-07T14:26:34.671826Z

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Observation 75521ad9-51f0-4163-8c45-f2906b55966c · outbound

This paper cites Equipocket: an e(3)-equivariant geometric graph neural network for ligand binding site prediction.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning Equipocket: an e(3)-equivariant geometric graph neural network for ligand binding site prediction

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:26:35.364327Z

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