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Paper Citation Record · LEDGER

ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2501.04284.

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

pith.paper-citation-record.v1
2501.04284 v2

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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:21:47.364742Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1c7cf9fe-7477-4645-b290-57c88f43d522 · inbound

MR-CLIP: Efficient Metadata-Guided Learning of MRI Contrast Representations cites this paper.

MR-CLIP: Efficient Metadata-Guided Learning of MRI Contrast Representations ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T23:21:47.364742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:21:47.364742Z digest=sha256:bd9633a9c919b343d6138c853e9a980392ade695051b35236d58acbd32cb7123

Observation 1700b994-ff94-428d-8e9e-23dc9fbb02df · inbound

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction cites this paper.

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T12:43:38.318518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:43:38.318518Z digest=sha256:c4580aeba9aafd9265e5d96feeca2f3234805274c2358122a0ca6aba1a0d4ab6

Observation e48ca55d-658a-4b20-b76b-6b14035aa33a · inbound

Active Learning for Conditional Generative Compressed Sensing cites this paper.

Active Learning for Conditional Generative Compressed Sensing ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-11T17:36:06.409347Z

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=2026-05-08T17:24:23.853637Z digest=sha256:3f51612e803c89d0fa354bbe8a9c4c0631db8a4a3a044f9dd2705b52c7bba585

Observation e7b8e519-e370-43f4-9c72-bd9f0ce7f11c · inbound

FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data cites this paper.

FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data ContextMRI: Enhancing Compressed Sensing MRI through Metadata Conditioning

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-07-01T05:35:25.050106Z

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=2026-07-01T05:32:13.269159Z digest=sha256:404652ba5a09a8ed2da6f355e50c55d397cc24f8734383f8e1c0467244b2843f