Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.12947.
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 2026-08-09T23:21:56.532486Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-09T15:26:53.591261Z
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 1de4c393-8eaf-4627-b6dc-e603240297d0 · inbound
A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models cites this paper.
A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T23:21:56.532486Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation baa5b8b6-c895-4a3c-a587-f24a6a8bfb1c · inbound
Emergent Stack Representations in Modeling Counter Languages Using Transformers cites this paper.
Emergent Stack Representations in Modeling Counter Languages Using Transformers Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-08-09T15:26:53.596955Z
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 7a0251cc-10a9-489a-9d22-0b937e61ea5d · inbound
Hierarchical Domain Generalization cites this paper.
Hierarchical Domain Generalization Transformer-Based Models Are Not Yet Perfect At Learning to Emulate Structural Recursion
Reference 87
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T20:54:11.042189Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.