Pith. sign in

Paper Citation Record · LEDGER

A Note on Over-Smoothing for Graph Neural Networks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 25 inbound Pith citation observations for arXiv:2006.13318.

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

pith.paper-citation-record.v1
2006.13318 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 25 of 25 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:11:39.160435Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T08:49:42.010484Z

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 abe5615e-6397-4a23-bc90-d6eccbec1f01 · inbound

Heterogeneous Sheaf Neural Networks cites this paper.

Heterogeneous Sheaf Neural Networks A Note on Over-Smoothing for Graph Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-23T20:58:26.730276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T20:57:34.082406Z digest=sha256:9a2a5f216128e88bc469cad829471aba2ee116ed6039e92657c5193a7ec7b24b

Observation a414c8a2-beef-4374-a888-43a4cf08a384 · inbound

Geometric GNNs for Charged Particle Tracking at GlueX cites this paper.

Geometric GNNs for Charged Particle Tracking at GlueX A Note on Over-Smoothing for Graph Neural Networks

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:11:39.160435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:11:39.160435Z digest=sha256:bcc899ad26663183100de5bd9d2b30cc084e15017b015ba09fbedb654fb32637

Observation 622366f4-bb0c-4cc6-baee-655ff236e03d · inbound

How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data? cites this paper.

How do Probabilistic Graphical Models and Graph Neural Networks Look at Network Data? A Note on Over-Smoothing for Graph Neural Networks

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T01:07:34.736049Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:07:34.736049Z digest=sha256:ec899b4999163f5ef2fc2da05eeaab94eee4e3cd50a69ddfca558a6492a7f5d2

Observation 322575a8-17f1-45a1-834a-d280c63a48e1 · inbound

Bridging Theory and Practice in Link Representation with Graph Neural Networks cites this paper.

Bridging Theory and Practice in Link Representation with Graph Neural Networks A Note on Over-Smoothing for Graph Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T21:35:07.857578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:35:07.857578Z digest=sha256:b591a6f692a3b66d1aa42caab4483157c89feb57d08fbc517c1f926958e05bf6

Observation 40db5b14-6da4-4aee-b708-3ace3a9ae556 · inbound

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows cites this paper.

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows A Note on Over-Smoothing for Graph Neural Networks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-05T23:39:46.043567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:39:46.043567Z digest=sha256:199e5ac3a4b765622a5afd1b3459b0d20a1a076aa8a0a6963610fd25b7fa6b6c

Observation bdabdcd1-bff2-4c12-bafc-04c07181b95e · inbound

Comment on "A Note on Over-Smoothing for Graph Neural Networks" cites this paper.

Comment on "A Note on Over-Smoothing for Graph Neural Networks" A Note on Over-Smoothing for Graph Neural Networks

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-05T10:25:45.787593Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T10:25:45.787593Z digest=sha256:a1b12e9dfe5c0303a83191db5b9a7f73ac16d80a4da217fecf52a2a6db085e1f

Observation cf700b82-eb71-4765-824d-87dffa65fbd7 · inbound

How Wide and How Deep? Mitigating Over-Squashing of GNNs via Channel Capacity Constrained Estimation cites this paper.

How Wide and How Deep? Mitigating Over-Squashing of GNNs via Channel Capacity Constrained Estimation A Note on Over-Smoothing for Graph Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-17T23:25:28.625201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-17T23:23:07.672908Z digest=sha256:1461d7efb24b6b8fbe5f1ad06ae56952e06c8cf89449dc8cba358e887e92014e

Observation 26bad750-b3ec-4d1f-afbc-3a9e7700dd7c · inbound

Learning from Historical Activations in Graph Neural Networks cites this paper.

Learning from Historical Activations in Graph Neural Networks A Note on Over-Smoothing for Graph Neural Networks

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-21T17:15:25.467255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-21T17:14:52.859473Z digest=sha256:8a2e0716a9c4dd028c4fc8cd4972fd11f9f47b2dd0c5df29e6d30a106772601c

Observation c6b523cf-922b-4a1c-ba8b-6bc3d9b57137 · inbound

Smoothness Errors in Dynamics Models and How to Avoid Them cites this paper.

Smoothness Errors in Dynamics Models and How to Avoid Them A Note on Over-Smoothing for Graph Neural Networks

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T07:27:32.243070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T07:23:07.669607Z digest=sha256:07500cb0edb1c5a5a4d109e10f8b4b465d30db8003492f90a9a7eee843e07f42

Observation dd899da5-6fbc-47cc-b94d-c206a2645be5 · inbound

Beyond ReLU: Bifurcation, Oversmoothing, and Topological Priors cites this paper.

Beyond ReLU: Bifurcation, Oversmoothing, and Topological Priors A Note on Over-Smoothing for Graph Neural Networks

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-02T22:56:38.772674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T22:56:38.772674Z digest=sha256:adc5fbd6b5a69e593790edafde0480bf6ebd97222e918fb75b2535a3714f052d

Observation 42219ca9-eb8d-4fdd-be3b-a3fd83f865d7 · inbound

A Mechanistic Analysis of Looped Reasoning Language Models cites this paper.

A Mechanistic Analysis of Looped Reasoning Language Models A Note on Over-Smoothing for Graph Neural Networks

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-11T09:41:03.018771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T15:53:19.680424Z digest=sha256:5800f838d07bf8f2f5dd70b5c271473621fd03b0d46c9b483f600149353c6d89

Observation 7d8c3f36-9bb2-404e-9eed-3bd7dda70c93 · inbound

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors cites this paper.

Learning Posterior Predictive Distributions for Node Classification from Synthetic Graph Priors A Note on Over-Smoothing for Graph Neural Networks

Reference 263

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:21:04.805127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-10T03:50:44.626261Z digest=sha256:8e803f3e09e4b601c9dbd2a31c93cd4ec9ea78ed9d263e133e153fd61db81063

Observation 7a6add99-3e9c-41b5-af6f-c1cf77ab9889 · inbound

Layer Embedding Deep Fusion Graph Neural Network cites this paper.

Layer Embedding Deep Fusion Graph Neural Network A Note on Over-Smoothing for Graph Neural Networks

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:41:10.214896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-08T08:22:06.951781Z digest=sha256:1e25aef4b6162e20bedd4a5690b6a532fe20c9d9893b3ee379294eb9ea82d5df

Observation 01bbc750-108e-45f2-ae09-0f31b308cec2 · inbound

Aspect-Aware Content-Based Recommendations for Mathematical Research Papers cites this paper.

Aspect-Aware Content-Based Recommendations for Mathematical Research Papers A Note on Over-Smoothing for Graph Neural Networks

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T00:46:12.998127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T14:19:18.282566Z digest=sha256:c2f61b0254c9c4ed1e3b9cae7be5d288f3bc7a057b1d102a0fdad4918a2760ee

Observation 09412db8-f76b-4fe4-b271-d250206a6b8e · inbound

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning cites this paper.

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning A Note on Over-Smoothing for Graph Neural Networks

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-12T07:56:27.392442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T01:31:19.576223Z digest=sha256:87577b0e8718e6dbf97207c18aa02f876a232b78e25cbd1cffe762219ace717b

Observation 8b6f1b69-1278-4e97-9229-098cf290e339 · inbound

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning cites this paper.

SACHI: Structured Agent Coordination via Holistic Information Integration in Multi-Agent Reinforcement Learning A Note on Over-Smoothing for Graph Neural Networks

Reference 58

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:39:10.766166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T22:34:46.440511Z digest=sha256:5ebe93276183a48871085a6cd797477258c6847614890c391296f5c888b3ccba

Observation 8fb699ff-ca29-4301-bd1d-7965373fe204 · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition A Note on Over-Smoothing for Graph Neural Networks

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-14T19:07:51.550122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-14T19:05:31.289091Z digest=sha256:e7cd77e343d995968bfb375397b0b5431df5c93654bb86c0ca09a26af8e6382b

Observation 4326657b-d397-4c87-85c7-a7569310223e · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition A Note on Over-Smoothing for Graph Neural Networks

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:45:05.601379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-30T21:43:50.425136Z digest=sha256:532b85460ea7dbc44ce1f4e80f39b4660189f822d3daef53a878ef3bdc3d36ee

Observation 42019845-f612-4759-8bf2-5269099c75f1 · inbound

Neural Point-Forms cites this paper.

Neural Point-Forms A Note on Over-Smoothing for Graph Neural Networks

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:02:36.572074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T15:00:51.826915Z digest=sha256:08feb927d6201d702139e4d73551f591570a9666063beaa54b818e4eacd0c5ce

Observation c48fbcdb-bac9-462b-8abd-88a2b610151a · inbound

Graph Hierarchical Recurrence for Long-Range Generalization cites this paper.

Graph Hierarchical Recurrence for Long-Range Generalization A Note on Over-Smoothing for Graph Neural Networks

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:08:17.756805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T13:06:49.896124Z digest=sha256:979453ccfd74bf279061c1cb974e95977cbe4e5f868c6f7d1d21d3ca766e03e6

Observation 1102a938-3f53-40aa-aa7d-d66f0f3feed9 · inbound

AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network cites this paper.

AGDN: Learning to Solve Traveling Salesman Problem with Anisotropic Graph Diffusion Network A Note on Over-Smoothing for Graph Neural Networks

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-07-04T00:09:14.385842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T21:29:20.129182Z digest=sha256:31b094a625901c348b2824aecc6dae7e2c5e3fafdf953cdbcac5d3c4cf005875

Observation 8b90488a-b86a-48ca-98e5-3e1de74bd5c0 · inbound

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation cites this paper.

Enhancing LLMs for Graph Tasks via Graph-aware LoRA Generation A Note on Over-Smoothing for Graph Neural Networks

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-07-04T08:49:42.012875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-26T10:59:25.867813Z digest=sha256:d26aab7f979306aef9452ebde9684e1d313f92217f17164ae0197db1983bf7d0

Observation dcdee1e8-e9d9-4186-9584-1c53a58a0f98 · inbound

From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks cites this paper.

From Diffusion to Reaction-Diffusion: A Dynamical-Systems View of Oversmoothing in Hypergraph Neural Networks A Note on Over-Smoothing for Graph Neural Networks

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-01T22:29:30.198124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T22:29:30.198124Z digest=sha256:b016aa943eec4ad846a0d2eddf7459d346bcae321510b5370cc94a7e328f641f

Observation 67464bd9-51e9-4640-9d03-397e515783e7 · inbound

Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement cites this paper.

Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement A Note on Over-Smoothing for Graph Neural Networks

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-01T06:31:19.346482Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T06:31:19.346482Z digest=sha256:2308921c2be82522cc1c7b9b5211c86e8ad305cdb8b1c25ee0ba186a44ffef24

Observation c40c02ee-b0aa-4b7a-855a-543092a66d82 · inbound

Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature cites this paper.

Local-Global Geometric Insights for Graph Neural Networks via Entropic Curvature A Note on Over-Smoothing for Graph Neural Networks

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-01T05:00:11.704197Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T05:00:11.704197Z digest=sha256:8a604721355c76f49d9ff62d10c70291ee7689107adc33f464184555a238b9f5