Paper Citation Record · LEDGER

Can Transformers Learn to Solve Problems Recursively?

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2305.14699.

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

pith.paper-citation-record.v1
2305.14699 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T19:58:59.148987Z

measured 1 of 1 external citation measurements

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

5
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 e7a67bdc-65d0-4a7d-acf5-5aec3d81c284 · inbound

Llemma: An Open Language Model For Mathematics cites this paper.

Llemma: An Open Language Model For Mathematics Can Transformers Learn to Solve Problems Recursively?

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-19T08:17:46.483868Z

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 c0bfd6f3-9a95-45f0-b536-fb6db3b6dce6 · inbound

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code cites this paper.

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code Can Transformers Learn to Solve Problems Recursively?

Reference 98

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:34:43.101455Z

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 c7f8ad79-2d7b-46c4-b4ae-704ec012de4b · inbound

Learning Model Successors cites this paper.

Learning Model Successors Can Transformers Learn to Solve Problems Recursively?

Reference 187

Resolution: unresolved; no resolver link, observed 2026-08-09T19:58:59.148987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79174ed3-6ec7-4911-8498-1c760448f352 · inbound

Code Simulation as a Proxy for High-order Tasks in Large Language Models cites this paper.

Code Simulation as a Proxy for High-order Tasks in Large Language Models Can Transformers Learn to Solve Problems Recursively?

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T04:32:43.094507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fcb04104-2c77-4aae-b4e9-cbcd486ef2d1 · inbound

Learning the symmetric group: large from small cites this paper.

Learning the symmetric group: large from small Can Transformers Learn to Solve Problems Recursively?

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:52:26.934686Z

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 efe172be-b5e5-463a-9970-9cd2c5f1795b · inbound

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task cites this paper.

Higher Embedding Dimension Creates a Stronger World Model for a Simple Sorting Task Can Transformers Learn to Solve Problems Recursively?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T08:56:15.153338Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b379b9a6-d7a3-4f3d-9a78-3c081bea9966 · inbound

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces cites this paper.

Correcting Influence: Unboxing LLM Outputs with Orthogonal Latent Spaces Can Transformers Learn to Solve Problems Recursively?

Reference 90

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T20:17:54.311771Z

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.