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Paper Citation Record · LEDGER

Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2008.08461.

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

pith.paper-citation-record.v1
2008.08461 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T06:01:01.079083Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T19:37:13.825386Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation b1ca00ea-6cab-43f2-a26c-72a51abe60f7 · inbound

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution cites this paper.

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-12T06:01:01.079083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T06:01:01.079083Z digest=sha256:96a5274796b4fdc4f4a8c9f32b01e0a5844d9224799a9cb47f91cd2c18fc9b40

Observation 613a8ab8-802b-4fcd-a08a-c3c8d475227f · inbound

EquAct: An SE(3)-Equivariant Multi-Task Transformer for Open-Loop Robotic Manipulation cites this paper.

EquAct: An SE(3)-Equivariant Multi-Task Transformer for Open-Loop Robotic Manipulation Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T13:35:52.950960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:35:52.950960Z digest=sha256:26b4042b578d0822f61fcd91c615ba35aabbe9a0cfc0c6f7031c60d5fe74eb06

Observation 08aa345a-c0a2-4c04-b98e-6ee19506a254 · inbound

SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space cites this paper.

SE(3)-Equivariant Diffusion Policy in Spherical Fourier Space Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T20:54:02.828809Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:54:02.828809Z digest=sha256:593fdf7e705ba3fd944a4d275cdd84061d88d44ca7937a88c7fd65376922780e

Observation 6370e15c-1e40-4b0e-8878-61afec3ac661 · inbound

A 3D Machine Learning based Volume Of Fluid scheme without explicit interface reconstruction cites this paper.

A 3D Machine Learning based Volume Of Fluid scheme without explicit interface reconstruction Relevance of Rotationally Equivariant Convolutions for Predicting Molecular Properties

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-06T19:37:13.830784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-06T19:37:13.765604Z digest=sha256:09fb69a8b50e03850dc70f647f612a428eb890333a37e572b7bf4109da03e2b0