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Paper Citation Record · LEDGER

Contextual Text Denoising with Masked Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1910.14080.

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

pith.paper-citation-record.v1
1910.14080 v2

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T13:29:54.834570Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T08:46:07.720113Z

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 fab4d098-24d5-4e6b-8945-64e04bde3f7a · inbound

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach cites this paper.

When LLM Agents Meet Graph Optimization: An Automated Data Quality Improvement Approach Contextual Text Denoising with Masked Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-18T08:46:07.722665Z

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=2026-05-18T08:45:51.992431Z digest=sha256:8f42581f382084677ab580f8dcd6d2b7644d9a64a68114d8df71a8852f7a0477

Observation 6268c423-a6f9-4581-8392-16098bae73e0 · inbound

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation cites this paper.

OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation Contextual Text Denoising with Masked Language Models

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-01T13:29:54.834570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T13:29:54.834570Z digest=sha256:a6831a5d96949782e5aa983447eb27985f0fe5a6648efc83c8d9a92da3d1dccd