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Paper Citation Record · LEDGER

Release of Pre-Trained Models for the Japanese Language

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2404.01657.

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

pith.paper-citation-record.v1
2404.01657 v1

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 2026-08-10T06:31:04.303077+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T09:45:05.825373Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T10:58:03.196096Z

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 13a42c5d-e0c3-44cd-9d5f-7333411418e8 · inbound

Image Score: Learning and Evaluating Human Preferences for Mercari Search cites this paper.

Image Score: Learning and Evaluating Human Preferences for Mercari Search Release of Pre-Trained Models for the Japanese Language

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-23T21:43:28.576844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T21:43:26.252406Z digest=sha256:8527cf9620382a803fa06dcdeffdb48397c40687c3e557ded7148f283bbc5b93

Observation 97f1756f-f98f-4fd3-91bb-0e7ee50f6fc6 · inbound

Establishing a Scale for Kullback-Leibler Divergence in Language Models Across Various Settings cites this paper.

Establishing a Scale for Kullback-Leibler Divergence in Language Models Across Various Settings Release of Pre-Trained Models for the Japanese Language

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T14:11:38.375678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-22T14:11:05.769830Z digest=sha256:fd89be45f154145e4a276ef93f7db5cbdf37413266be3a40e9d2baa6bb46ee56

Observation 42f00e3f-979e-4681-bd13-3e9a850f2005 · inbound

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models cites this paper.

Investigating the Representation of Backchannels and Fillers in Fine-tuned Language Models Release of Pre-Trained Models for the Japanese Language

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-05-18T14:11:27.654840Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-18T14:07:26.348545Z digest=sha256:d0f00c3a73b4a603a79ef950af59da7beef50802c25e847e3f0373c2d6dd3bfd

Observation 41cd1eb8-187e-487b-9e83-24f32098d20e · inbound

I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System cites this paper.

I Understand How You Feel: Enhancing Deeper Emotional Support Through Multilingual Emotional Validation in Dialogue System Release of Pre-Trained Models for the Japanese Language

Reference 50

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T10:58:03.197545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-27T09:45:05.825373Z digest=sha256:d1c587818131874f370596205d2fa57a3779969babc6f41ea6fa9e3a14307be5