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Paper Citation Record · LEDGER

Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.06228.

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

pith.paper-citation-record.v1
2405.06228 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:06:35.366451Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-09T20:52:32.981169Z

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 480de709-6fcf-4f80-b114-810fcce08115 · inbound

Deformable Mamba for Wide Field of View Segmentation cites this paper.

Deformable Mamba for Wide Field of View Segmentation Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-12T13:06:35.366451Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:06:35.366451Z digest=sha256:181d7baa2d079c869a79094a8d02f80d1e7e2ca4ec6ddb1a94802e890e4ced74

Observation 68bec338-4bba-4c46-9888-2dea44869d8f · inbound

SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation cites this paper.

SegMAN: Omni-scale Context Modeling with State Space Models and Local Attention for Semantic Segmentation Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T14:32:17.546663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:32:17.546663Z digest=sha256:1ff23f342a52f1b7ca180770eb2ba13ee7dd237c31c7718ca3fb82ee05fdfc7a

Observation 2b66a459-d47c-46cc-af2a-a3a12e957a06 · inbound

ContextFormer: Redefining Efficiency in Semantic Segmentation cites this paper.

ContextFormer: Redefining Efficiency in Semantic Segmentation Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation

Reference 48

Resolution
verified exact
local_arxiv, observed 2026-08-09T20:52:32.986482Z

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=2026-08-09T20:52:32.843334Z digest=sha256:c309b5dee76c66d10b137408ef767732cfcc8f3d4fba8724601e8d9d11424b88