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Paper Citation Record · LEDGER

Weighted Transformer Network for Machine Translation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1711.02132.

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

pith.paper-citation-record.v1
1711.02132 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-14T10:49:57.470750Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T08:04:31.366904Z

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 ef5c93e9-fa54-4e54-b092-f0577453bd55 · inbound

Universal Transformers cites this paper.

Universal Transformers Weighted Transformer Network for Machine Translation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-07-04T22:19:34.622408Z

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=pdf_text observed=2026-05-13T08:04:31.337298Z digest=sha256:a02bc6f114cf64d5cb6fe53b3a9571dd3e08006fd6285cf0d74a8c829b33f230

Observation 9323885b-2be6-4624-a388-ed9bf2378d4c · inbound

Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure cites this paper.

Multiresolution Transformer Networks: Recurrence is Not Essential for Modeling Hierarchical Structure Weighted Transformer Network for Machine Translation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T10:49:57.470750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T10:49:57.470750Z digest=sha256:100e6bd53b2611099d20f31613a34df66dc83c17b00c77e92b8715b666aae3fd

Observation c1de6a60-e69e-4882-9d42-570071db5987 · inbound

Improving Multi-Head Attention with Capsule Networks cites this paper.

Improving Multi-Head Attention with Capsule Networks Weighted Transformer Network for Machine Translation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T06:05:18.133736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T06:05:18.133736Z digest=sha256:9f2ff4560c15b15b8db26ae5136d65c8e1635654916bb7259b457b445ff3b02a