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Paper Citation Record · LEDGER

ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1512.05193.

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

pith.paper-citation-record.v1
1512.05193 v4

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 2026-08-14T12:54:54.993657Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-14T12:34:12.069420Z

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 6966434b-b4ad-469b-9c41-66b0e72a2842 · inbound

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification cites this paper.

A Sensitivity Analysis of Attention-Gated Convolutional Neural Networks for Sentence Classification ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-14T12:54:54.993657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T12:54:54.993657Z digest=sha256:cde437844675b4e8894ac16057b15759f83d2fdb34f931495b155b7fb78959ed

Observation 29c1d9d6-5fe5-408d-8c59-79c08db9e300 · inbound

Representing text as abstract images enables image classifiers to also simultaneously classify text cites this paper.

Representing text as abstract images enables image classifiers to also simultaneously classify text ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-14T12:34:12.076994Z

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=2026-08-14T12:34:11.941420Z digest=sha256:f1a53606224e316de46a90148142e4a08709132bcd2d653d364d7537870b28cc