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Paper Citation Record · LEDGER

Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2401.11611.

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

pith.paper-citation-record.v1
2401.11611 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-12T03:57:58.024137Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T06:46:52.467013Z

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 a395d79c-f1b9-4fa2-b7d1-11d06e190055 · inbound

LASER: Learning Active Sensing for Continuum Field Reconstruction cites this paper.

LASER: Learning Active Sensing for Continuum Field Reconstruction Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T12:31:02.510094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T03:35:23.240677Z digest=sha256:cc12cb4931ae5ece3405f21a7847cf954c868c39c58a2342b6e730e1aa540d91

Observation 52df1ca7-bcc0-440b-86b3-3e595b12ac66 · inbound

WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain cites this paper.

WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain Continuous Field Reconstruction from Sparse Observations with Implicit Neural Networks

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-12T06:46:52.469478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T03:57:58.024137Z digest=sha256:38d4cc08ff3bf79508751d302c5537a91a3e01949a9c8dfc231cb3bfb1bed8e0