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Paper Citation Record · LEDGER

Pre-trained Language Model Representations for Language Generation

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1903.09722.

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

pith.paper-citation-record.v1
1903.09722 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:18:47.694598Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T11:49:47.272959Z

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 7137753a-52c1-4a84-8888-3ff73621fcc4 · inbound

Towards Making the Most of BERT in Neural Machine Translation cites this paper.

Towards Making the Most of BERT in Neural Machine Translation Pre-trained Language Model Representations for Language Generation

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T13:18:47.694598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:18:47.694598Z digest=sha256:620e59885a8015421b7d4e6724825651e214d0d16e4902c266ef96d0f4a85352

Observation de5d6993-586b-4cff-b695-92f97f43d2d1 · inbound

Denoising based Sequence-to-Sequence Pre-training for Text Generation cites this paper.

Denoising based Sequence-to-Sequence Pre-training for Text Generation Pre-trained Language Model Representations for Language Generation

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:49:47.277691Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-08-14T11:49:46.901286Z digest=sha256:bddf812fe032e8ed24341202ddcfad3bc819cbaf084ef47eb3622b907b348da6