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Paper Citation Record · LEDGER

Enhanced LSTM for Natural Language Inference

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1609.06038.

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

pith.paper-citation-record.v1
1609.06038 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:00:56.854471Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T00:46:30.533388Z

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 1adf7aac-5b89-493f-a352-dcad4cb78e07 · inbound

To Tune or Not To Tune? How About the Best of Both Worlds? cites this paper.

To Tune or Not To Tune? How About the Best of Both Worlds? Enhanced LSTM for Natural Language Inference

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-05-25T00:46:30.537243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-25T00:45:10.865484Z digest=sha256:c5cbec8668e1bff158ccf4907466c1c84ae206e6c1596bbb9ab9b35df0192097

Observation afdf6c4d-60e4-4c6c-90dd-4518d4a76f72 · inbound

Fake News Detection as Natural Language Inference cites this paper.

Fake News Detection as Natural Language Inference Enhanced LSTM for Natural Language Inference

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-24T20:46:21.633923Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T20:46:10.915616Z digest=sha256:ef4fd34696b56089c6384798f1b974763a6a63e959d6482660430c3b9b024f9f

Observation 74bf6b10-d955-4e66-b19d-67bbeb0d809b · inbound

PubMedQA: A Dataset for Biomedical Research Question Answering cites this paper.

PubMedQA: A Dataset for Biomedical Research Question Answering Enhanced LSTM for Natural Language Inference

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-23T18:42:51.240311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-23T18:42:51.182937Z digest=sha256:b1a0da907aff1d92e93b0314a28ec2afb072f656404ab27177409bf0fecaadb6

Observation c6d5dfee-8c42-440b-826f-fc6a1e6a023f · inbound

Bias in Large Language Models: Origin, Evaluation, and Mitigation cites this paper.

Bias in Large Language Models: Origin, Evaluation, and Mitigation Enhanced LSTM for Natural Language Inference

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-23T17:08:12.268462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-23T17:08:09.267577Z digest=sha256:9e9890608d176a2e6c35536400320f6c6de977406eecc7c8599aae35d8f32d05

Observation 18c1400a-d0eb-47f6-ac84-19d653b48a3a · inbound

Adversarial Text Generation with Dynamic Contextual Perturbation cites this paper.

Adversarial Text Generation with Dynamic Contextual Perturbation Enhanced LSTM for Natural Language Inference

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T05:00:56.854471Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:00:56.854471Z digest=sha256:96ea65f1613808cc50f2a0ac6593e4867b0a577aaf30c3d25b07813635833757

Observation b2cc700a-b944-43fe-95f0-a4fdcb74ca89 · inbound

Multi-Granularity Reasoning for Natural Language Inference cites this paper.

Multi-Granularity Reasoning for Natural Language Inference Enhanced LSTM for Natural Language Inference

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-12T19:07:54.710156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T19:07:54.710156Z digest=sha256:8a9ade3959c7259a0c0425da0641c809ea904c837004f38f7ec6019f40367619