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Paper Citation Record · LEDGER

Graph Mamba: Towards Learning on Graphs with State Space Models

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2402.08678.

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

pith.paper-citation-record.v1
2402.08678 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:29:54.674105Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:13:30.782773Z

Reference resolution

0 of 0 outbound references displayed

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  • 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 1d48cc09-e347-45f2-a557-80b5ab609253 · inbound

A Survey of Mamba cites this paper.

A Survey of Mamba Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.784508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-05-23T22:09:19.917854Z digest=sha256:4866950b4bd8863ab981e26a202f194fed16fd2a28ac9560f309239611147275

Observation fcc2d5d8-d305-4745-bf0b-a5497942a5e7 · inbound

On the Efficiency of NLP-Inspired Methods for Tabular Deep Learning cites this paper.

On the Efficiency of NLP-Inspired Methods for Tabular Deep Learning Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-12T12:29:54.674105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:29:54.674105Z digest=sha256:e2549ca0927c92683db974c3fe44bf6ba05ae2cb0e73753e902fd3baf63e1b40

Observation 667700ff-ecad-40db-a924-2a60172eead8 · inbound

MPSI: Mamba enhancement model for pixel-wise sequential interaction Image Super-Resolution cites this paper.

MPSI: Mamba enhancement model for pixel-wise sequential interaction Image Super-Resolution Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T19:00:18.702581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:00:18.702581Z digest=sha256:28481815b375f691728cdadf1d3313b912e3a688eb38db83368e049ea3deee45

Observation 9091840c-fe2f-4c82-9432-d2effe9c0b35 · inbound

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models cites this paper.

DG-Mamba: Robust and Efficient Dynamic Graph Structure Learning with Selective State Space Models Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T18:14:49.550935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T18:14:49.550935Z digest=sha256:7f65298344f1dd9898257b10d67601152765d393e5e277060544805cf884a465

Observation 5e07d97c-57fc-441a-b32b-c84cfaab3435 · inbound

A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers cites this paper.

A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-11T15:08:15.695546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T15:08:15.695546Z digest=sha256:bb79d22949829fe69bc215baac8da3b4e28122bb96ac07d123d86b75fac3ea81

Observation ee1e475a-6f93-4fa2-b8ad-d750a4dc079b · inbound

MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights cites this paper.

MOL-Mamba: Enhancing Molecular Representation with Structural & Electronic Insights Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-11T10:36:38.015971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T10:36:38.015971Z digest=sha256:99dde449c908db63f06b99d15fc3003d44ca9d51418a0998b9202848226914ef

Observation 3172955f-6e79-431c-bc0a-6356eb2ed1aa · inbound

GRAMA: Adaptive Graph Autoregressive Moving Average Models cites this paper.

GRAMA: Adaptive Graph Autoregressive Moving Average Models Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-10T16:57:29.019297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:57:29.019297Z digest=sha256:2a69407c658c2f4373c12564528ba3752c73354d0268706734202690a3d0de34

Observation 6dae5f2d-2a1d-4728-98a1-da8bebba7c4c · inbound

MV-GMN: State Space Model for Multi-View Action Recognition cites this paper.

MV-GMN: State Space Model for Multi-View Action Recognition Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-10T15:37:30.362130Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T15:37:30.362130Z digest=sha256:b157d959fa82f13b5a39f41a893fa9576dd8efe839e62a6176169116da732d48

Observation 904a9ded-b419-4d13-9683-b0a44098dd15 · inbound

CD-Lamba: Boosting Remote Sensing Change Detection via a Cross-Temporal Locally Adaptive State Space Model cites this paper.

CD-Lamba: Boosting Remote Sensing Change Detection via a Cross-Temporal Locally Adaptive State Space Model Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-10T14:19:14.422706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:19:14.422706Z digest=sha256:4faef937b20c57ba20bf58d6ae71ade344ad7090d3c94db807e937c7570749e4

Observation e8d69591-2253-4248-a0e6-b27710490738 · inbound

Improving the Effective Receptive Field of Message-Passing Neural Networks cites this paper.

Improving the Effective Receptive Field of Message-Passing Neural Networks Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T12:57:31.203065Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:57:31.203065Z digest=sha256:f1480fdb78d70173baf03e81bd9172fdfa8bbf793422a89ac0dfdd24fa564b90

Observation b1160578-65bc-4b7b-8698-15c37612d9ba · inbound

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

TANGO: Graph Neural Dynamics via Learned Energy and Tangential Flows Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-05T23:39:46.010872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T23:39:46.010872Z digest=sha256:082fce09bc111b1e5e0990caee03d6f60d3186d64c79cc4ef00232546655e187

Observation 4cf74c9b-aa58-4769-bb3a-72e4e02c8e75 · inbound

Black-Mamba: Biologically-Inspired Leaky Accumulation for Conceptual Knowledge under Distribution Drift cites this paper.

Black-Mamba: Biologically-Inspired Leaky Accumulation for Conceptual Knowledge under Distribution Drift Graph Mamba: Towards Learning on Graphs with State Space Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-01T14:02:33.548205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:02:33.548205Z digest=sha256:9a1ab547ae7ce695b824d32ccd68a8c1f5b4be461acb514f332d93c468ce4c6e