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Paper Citation Record · LEDGER

Global Encoding for Abstractive Summarization

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1805.03989.

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

pith.paper-citation-record.v1
1805.03989 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 2026-08-17T06:30:58.91139+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T15:19:01.326532Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T11:49:47.190518Z

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 d18b9ea0-fe9c-4fe1-a56d-4c3275860b83 · inbound

Deep Neural Network for Semantic-based Text Recognition in Images cites this paper.

Deep Neural Network for Semantic-based Text Recognition in Images Global Encoding for Abstractive Summarization

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-14T15:19:01.326532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T15:19:01.326532Z digest=sha256:37af57a3ff385a5e99340082d3635edb7ddbc4f7597942248afb547a5b809b2e

Observation fede491c-cbb7-4654-91bb-d45fbcf3e4f3 · inbound

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

Denoising based Sequence-to-Sequence Pre-training for Text Generation Global Encoding for Abstractive Summarization

Reference 35

Resolution
verified exact
local_arxiv, observed 2026-08-14T11:49:47.197397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-14T11:49:46.973807Z digest=sha256:ab167163badfc660a6e675f7f53cbef6a69f017d90edb84fbe35134a13572262