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Paper Citation Record · LEDGER

An Empirical Exploration of Curriculum Learning for Neural Machine Translation

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1811.00739.

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

pith.paper-citation-record.v1
1811.00739 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 2026-08-06T06:34:29.942622+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:43:17.982750Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T05:31:24.190632Z

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 b6991e98-9894-4b12-8188-cf7dc99e0682 · inbound

Estimating Machine Translation Difficulty cites this paper.

Estimating Machine Translation Difficulty An Empirical Exploration of Curriculum Learning for Neural Machine Translation

Reference 2019

Resolution
malformed identifier
no resolver link, observed 2026-08-05T20:43:17.982750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:43:17.982750Z digest=sha256:a5ee0f5f31b464ac4f2a04635dfc02f83d9915fb211387a81c905c8d0778659a

Observation 308faac7-08db-435b-a034-2a8115181cf9 · inbound

The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently cites this paper.

The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently An Empirical Exploration of Curriculum Learning for Neural Machine Translation

Reference 109

Resolution
verified exact
arxiv_id, observed 2026-07-04T23:10:27.661515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-05-12T05:27:11.761971Z digest=sha256:1d6c540121ca9fe5121ac15a133e4262b1c77f1c152a40dd9959b369e50dba4b