Paper Citation Record · LEDGER

Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:1606.01305.

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

pith.paper-citation-record.v1
1606.01305 v4

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 2026-08-12T06:34:41.77262+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T13:44:56.476409Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-05-25T13:45:53.272803Z

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 76bbc748-9f6f-424c-822a-5f69f2456877 · inbound

Pointer Sentinel Mixture Models cites this paper.

Pointer Sentinel Mixture Models Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:10:32.275806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0565f779-3a41-43cb-8989-09119edb850b · inbound

ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network cites this paper.

ARMIN: Towards a More Efficient and Light-weight Recurrent Memory Network Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-25T13:45:53.276831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 9050a514-2ef9-4bf8-a628-31157810eee6 · inbound

R-Transformer: Recurrent Neural Network Enhanced Transformer cites this paper.

R-Transformer: Recurrent Neural Network Enhanced Transformer Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-24T22:56:26.232048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 99add77e-1a44-4f6b-b734-005b95635f94 · inbound

DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks cites this paper.

DropAttention: A Regularization Method for Fully-Connected Self-Attention Networks Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-24T16:24:40.654846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 44df0eb1-9021-4ddd-a1eb-438563f05c30 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-05-19T20:28:39.163115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation ece6e287-8bc3-47a2-a22b-4a0cc7d1788a · inbound

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models cites this paper.

One Step Forward and K Steps Back: Better Reasoning with Denoising Recursion Models Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations

Reference 177

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T11:05:09.085928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.