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Paper Citation Record · LEDGER

Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2304.11461.

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

pith.paper-citation-record.v1
2304.11461 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 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 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:47:16.521477Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T12:28:06.995990Z

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 2a77d1bf-a7af-4b75-b019-bdbb88e37ab5 · inbound

CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data cites this paper.

CNN-LSTM Hybrid Model for AI-Driven Prediction of COVID-19 Severity from Spike Sequences and Clinical Data Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T12:47:16.521477Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:47:16.521477Z digest=sha256:8852f32bb57ff60e4a6ae24c3bfc17d00076916f9de5c47c2b4783955d7e56bf

Observation 1732ac80-c8ee-4b2d-8150-03c57b1290b4 · inbound

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings cites this paper.

Predicting Post-Traumatic Epilepsy from Clinical Records using Large Language Model Embeddings Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:20:22.604484Z

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=2026-05-10T12:17:54.168604Z digest=sha256:b47e099bb13df6d850bdef7a415ec647988156ac97d650fef03681221eba21bc

Observation 52a80e9a-7a67-456b-ae6c-d0f250a4342c · inbound

Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling cites this paper.

Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T10:54:36.554083Z

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=2026-06-30T10:49:53.048960Z digest=sha256:e0b68c65130c3d8da13b00101f1fdb8b277da2a1e8400e929c8e6800a23076d0

Observation 2236030c-bb8c-4658-be94-1dff568da704 · inbound

Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling cites this paper.

Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T22:17:25.097135Z

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=2026-07-02T22:13:26.491273Z digest=sha256:b0352148346ac472b9bea6247c6bd9a784857f4659075e0362c7806bc9c13ed3

Observation cc5e3d6d-e8a8-4bd2-b71f-4399cff18112 · inbound

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation cites this paper.

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation Recurrent Neural Networks and Long Short-Term Memory Networks: Tutorial and Survey

Reference 27

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T12:28:06.998299Z

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=2026-07-03T12:24:53.884439Z digest=sha256:472aff2bd55bfcb81ade02e091fdfb2a084512587ec4d8ce431e26070b529ac4