Pith. sign in

Paper Citation Record · LEDGER

Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2110.02905.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2110.02905 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:33:49.253471Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a90f454c-95c3-4cd0-aeed-dbf05560c7c7 · inbound

STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation cites this paper.

STFlow: Data-Coupled Flow Matching for Geometric Trajectory Simulation Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:33:49.253471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:33:49.253471Z digest=sha256:82985e863ef83496df22a120427aee80641ba6b1e937516da8918431f66ff1eb

Observation bc5545c0-a889-4842-9592-6b9fb88dc5d3 · inbound

Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks cites this paper.

Thickness-aware E(3)-Equivariant 3D Mesh Neural Networks Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T13:55:14.060146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:55:14.060146Z digest=sha256:5d38dfb91412a4abb4d8463cbdb22af82536b1487f5fd5271a123d06419ae7d4

Observation cdf013ab-c78c-465e-8837-c69728fc5522 · inbound

Cosmology with Topological Deep Learning cites this paper.

Cosmology with Topological Deep Learning Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:13.611854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:13.611854Z digest=sha256:4071773408fc1fd5ae635184ed39cb681c4732c723f331c3f9e23deef83f2844

Observation 39f847c9-8316-4309-867c-d27094515bf8 · inbound

DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules cites this paper.

DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T05:14:41.031080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:14:41.031080Z digest=sha256:95e58dbececa619d1ade30fb1cd15d526828f7efe3969afcdba4169bee7e5ae5

Observation e8321533-fd03-4df0-bfb9-33e9d65ff7d5 · inbound

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending cites this paper.

cMALC-D: Contextual Multi-Agent LLM-Guided Curriculum Learning with Diversity-Based Context Blending Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T14:49:53.084615Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:49:53.084615Z digest=sha256:7a4a1d75ad1fc5e6db9e06181380216c8b4c562be97b33113b4e3ce86f90095a

Observation bd7abdfb-4a3f-471d-b054-01ba5f90cc62 · inbound

Bayesian Prior Construction for Uncertainty Quantification in First-Principles Statistical Mechanics cites this paper.

Bayesian Prior Construction for Uncertainty Quantification in First-Principles Statistical Mechanics Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-04T22:36:20.082737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T22:36:20.082737Z digest=sha256:fe9fb123ad7925ef82dc2604ac000b9cab7721dbb3a32731da3554e67ace7eb9

Observation 036bb212-8138-47cc-a7fd-da9043e3c1e1 · inbound

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks cites this paper.

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:46:23.345033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T12:45:28.458804Z digest=sha256:f6440962d6dc765f831171ce111082d307e8042506b13d5ed6c88d06f2523b76

Observation e321fce4-0107-407e-8d9c-b2ef8dbd351e · inbound

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 Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 65

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:02:31.603361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T10:01:16.498310Z digest=sha256:fc4b240f5b89edd253695ac8ff1e35e8cbf751c9e79dba632db017b61e226c67

Observation 0cfd1eb3-8411-4511-8726-cdb29e97c889 · inbound

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics cites this paper.

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 13

Resolution
unresolved
no resolver link, observed 2026-07-13T12:05:54.442913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T12:05:54.442913Z digest=sha256:85038f33f20a436464766029b29917892e84fdec8ed397b4955134c09c5f8c37

Observation e0e8f0be-3b98-422c-b65c-abb9004d88e1 · inbound

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 Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-15T03:09:43.925689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-15T03:05:14.435776Z digest=sha256:b98ea42011e0e858a4aa4247e60bb8e55f9cb2d0a11b18a43face8747da1391b

Observation cb5ea9e5-d795-4029-b29a-95522d124504 · inbound

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems cites this paper.

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 152

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:37:29.947866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T17:07:27.417845Z digest=sha256:b365b310a6ac8316183274882566764a4812e86584a1a71be7cb4f2fba04a93f

Observation d7083180-5b0c-4685-859c-9cd38fc0b163 · inbound

Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening cites this paper.

Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T02:09:22.463380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-26T20:00:57.283053Z digest=sha256:1f7bd4c435ca0684ac1900d3a65f617c4d8d23b4cb06de8bd8fb90362117a88a

Observation 20460b72-18ba-4465-88f8-f64d4fd1cf92 · inbound

Protein Representation Learning with Secondary-Structure and Energy-Filtered Hydrogen-Bond Graphs cites this paper.

Protein Representation Learning with Secondary-Structure and Energy-Filtered Hydrogen-Bond Graphs Geometric and Physical Quantities Improve E(3) Equivariant Message Passing

Reference 8

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T16:48:40.348815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-27T05:00:01.885867Z digest=sha256:405900007bcc61ff7771fb2e813b63a6d17bccfe76eeccf4d3346bea2c4d70f4