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Paper Citation Record · LEDGER

Neural Machine Translation with Supervised Attention

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1609.04186.

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

pith.paper-citation-record.v1
1609.04186 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 2026-08-22T06:32:14.747728+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:31:01.428314Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:07:42.651682Z

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 60ff0047-844e-48a0-95e6-6ee5b3f04f13 · inbound

Regularized Context Gates on Transformer for Machine Translation cites this paper.

Regularized Context Gates on Transformer for Machine Translation Neural Machine Translation with Supervised Attention

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T10:31:01.428314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T10:31:01.428314Z digest=sha256:66652e095a56e52ce868dfbaf7791faaefa3555dd35d41e50afd7ff2084c795e

Observation 914e7f33-327e-477c-ad22-87460706b8f3 · inbound

SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Modeling cites this paper.

SemToken: Semantic-Aware Tokenization for Efficient Long-Context Language Modeling Neural Machine Translation with Supervised Attention

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:07:42.713806Z

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=2026-08-05T18:07:39.657701Z digest=sha256:0d0c1fb0574e1d5cb8041d77767972107eed67206c0908edc56afb3e85bf6152