Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1911.03329.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T15:26:53.468162Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
30
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 9e0afae2-e353-415f-98b2-a8981e4560a6 · inbound
Emergent Stack Representations in Modeling Counter Languages Using Transformers cites this paper.
Emergent Stack Representations in Modeling Counter Languages Using Transformers Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T15:26:53.468162Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 384f50d2-5795-4dc5-b3e1-36b83e334658 · inbound
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach cites this paper.
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages
Reference 152
- Resolution
- verified exact
- arxiv_id, observed 2026-05-12T15:39:41.244973Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation ba9bdc28-fc1b-436e-be43-ee771ae98c20 · inbound
On the Emergence of Syntax by Means of Local Interaction cites this paper.
On the Emergence of Syntax by Means of Local Interaction Memory-Augmented Recurrent Neural Networks Can Learn Generalized Dyck Languages
Reference 32
- Resolution
- malformed identifier
- arxiv_id, observed 2026-05-11T12:06:01.193818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.