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Paper Citation Record · LEDGER

Verbalized Machine Learning: Revisiting Machine Learning with 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:2406.04344.

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

pith.paper-citation-record.v1
2406.04344 v3

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 2026-08-08T21:45:45.470962Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:20:25.110915Z

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 1045e54b-a72d-44d0-a6ec-35c66fa8dbae · inbound

Generating Symbolic World Models via Test-time Scaling of Large Language Models cites this paper.

Generating Symbolic World Models via Test-time Scaling of Large Language Models Verbalized Machine Learning: Revisiting Machine Learning with Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-08T21:45:45.470962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T21:45:45.470962Z digest=sha256:d1e3efcf72e52868e7f1b4e29612ce6b7c939d55c73215f1f1996a018e82ee6d

Observation 9a5a44ed-00f3-4f90-9f69-c60138bf1188 · inbound

CoReVAD: A Contextual Reasoning Framework for Training-Free Video Anomaly Detection cites this paper.

CoReVAD: A Contextual Reasoning Framework for Training-Free Video Anomaly Detection Verbalized Machine Learning: Revisiting Machine Learning with Language Models

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:20:25.113569Z

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=2026-05-25T05:17:10.587303Z digest=sha256:56a60ff4ec85dc9813cac85cc4a5212ad284dfcc46cbf736fd397c43116cbffa