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Paper Citation Record · LEDGER

A Survey on Low-Resource Neural Machine Translation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2107.04239.

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

pith.paper-citation-record.v1
2107.04239 v1

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 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T23:31:10.071627Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-12T04:51:34.786812Z

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 b313099b-09cf-4fa5-85a7-0a4a82e73b76 · inbound

From Priest to Doctor: Domain Adaptation for Low-Resource Neural Machine Translation cites this paper.

From Priest to Doctor: Domain Adaptation for Low-Resource Neural Machine Translation A Survey on Low-Resource Neural Machine Translation

Reference 45

Resolution
verified exact
local_arxiv, observed 2026-08-12T04:51:34.793498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=arxiv_source observed=2026-08-12T04:51:34.360721Z digest=sha256:9cac041cc5c723d93688c8b3caf0e78f05f961b98070480cc5a6cd4dd7baae29

Observation 5b601e18-1e59-4893-aba6-179090edc06e · inbound

Overcoming Data Scarcity in Generative Language Modelling for Low-Resource Languages: A Systematic Review cites this paper.

Overcoming Data Scarcity in Generative Language Modelling for Low-Resource Languages: A Systematic Review A Survey on Low-Resource Neural Machine Translation

Reference 109

Resolution
unresolved
no resolver link, observed 2026-08-15T23:31:10.071627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T23:31:10.071627Z digest=sha256:975accc1314d18896dba7069f6cc4eb978ec754b82833f0de7de926da688cde7