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Paper Citation Record · LEDGER

RS-Mamba for Large Remote Sensing Image Dense Prediction

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.02668.

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

pith.paper-citation-record.v1
2404.02668 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:56:58.193426Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T22:13:30.877226Z

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 39b4885d-e988-43d2-bb6a-4637c1a510e7 · inbound

A Survey of Mamba cites this paper.

A Survey of Mamba RS-Mamba for Large Remote Sensing Image Dense Prediction

Reference 239

Resolution
verified exact
arxiv_id, observed 2026-05-23T22:13:30.879678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-23T22:09:19.917854Z digest=sha256:00be706981ceca0ff60cb07cb1fd1f070eabb1163f31f2bc67953a5c58dea6d9

Observation e9828d94-1dcf-4752-82b9-0f151c6460dc · inbound

SAMamba: Adaptive State Space Modeling with Hierarchical Vision for Infrared Small Target Detection cites this paper.

SAMamba: Adaptive State Space Modeling with Hierarchical Vision for Infrared Small Target Detection RS-Mamba for Large Remote Sensing Image Dense Prediction

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T12:56:58.193426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:56:58.193426Z digest=sha256:54731910619310a825260109c06513a4ab30909fc8c060f20960a1bbe2cfd5b2

Observation ac3c6db3-18da-4445-9958-100ce368a92a · inbound

AtrousMamaba: An Atrous-Window Scanning Visual State Space Model for Remote Sensing Change Detection cites this paper.

AtrousMamaba: An Atrous-Window Scanning Visual State Space Model for Remote Sensing Change Detection RS-Mamba for Large Remote Sensing Image Dense Prediction

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T15:20:44.946144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T15:20:44.946144Z digest=sha256:120d90ef9060e92b5b69e7929d520fbb26822beb8c0f4d1c53217a68c3024b68

Observation fb722b31-b9f4-40c2-bb2f-83b292959cb9 · inbound

DGSSM: Diffusion guided state-space models for multimodal salient object detection cites this paper.

DGSSM: Diffusion guided state-space models for multimodal salient object detection RS-Mamba for Large Remote Sensing Image Dense Prediction

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-05-10T05:46:10.315550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T05:43:32.521715Z digest=sha256:042f8cca82ebaa12cc9b00f7296b8bd5bfd47dae8dc4e13e91f3a84b8290656c

Observation 379719e4-906f-4272-82ef-541eeddff28c · inbound

A Controlled Benchmark of Visual State-Space Backbones with Domain-Shift and Boundary Analysis for Remote-Sensing Segmentation cites this paper.

A Controlled Benchmark of Visual State-Space Backbones with Domain-Shift and Boundary Analysis for Remote-Sensing Segmentation RS-Mamba for Large Remote Sensing Image Dense Prediction

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T03:14:08.335991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T03:09:49.136433Z digest=sha256:3ed7f8aa2d971e618fe35ac641d7a48e15ea397c32f0b2ea180c55a24ba89ad5