Paper Citation Record · LEDGER

Auto-Regressive Next-Token Predictors are Universal Learners

As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2309.06979.

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

pith.paper-citation-record.v1
2309.06979 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T06:26:56.954432Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T22:47:36.908385Z

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 b116862d-e901-4e6b-bfe6-4511396b3db3 · inbound

Deep sequence models tend to memorize geometrically; it is unclear why cites this paper.

Deep sequence models tend to memorize geometrically; it is unclear why Auto-Regressive Next-Token Predictors are Universal Learners

Reference 114

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:40:36.300354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation ac6568ee-b235-4975-b97e-6041972a2a8a · inbound

Learning to Execute Graph Algorithms Exactly with Graph Neural Networks cites this paper.

Learning to Execute Graph Algorithms Exactly with Graph Neural Networks Auto-Regressive Next-Token Predictors are Universal Learners

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-03T06:26:56.954432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 055f5a41-18a0-406e-9739-07bc0769c634 · inbound

Sample Complexity of Autoregressive Reasoning: Chain-of-Thought vs. End-to-End cites this paper.

Sample Complexity of Autoregressive Reasoning: Chain-of-Thought vs. End-to-End Auto-Regressive Next-Token Predictors are Universal Learners

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:56:03.973938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 991ced40-62b3-41d4-a320-d58dc96fbe38 · inbound

Continuous Latent Diffusion Language Model cites this paper.

Continuous Latent Diffusion Language Model Auto-Regressive Next-Token Predictors are Universal Learners

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:11.115920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 138e46b6-2c65-4e15-8b31-ae43615224ec · inbound

A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning cites this paper.

A Theory of Online Learning with Autoregressive Chain-of-Thought Reasoning Auto-Regressive Next-Token Predictors are Universal Learners

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:58.600104Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 18ab5746-ac34-473a-9338-82489b82ced7 · inbound

Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers cites this paper.

Lost in Tokenization: Fundamental Trade-offs in Graph Tokenization for Transformers Auto-Regressive Next-Token Predictors are Universal Learners

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:04:41.425565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 49a72d71-5ec1-460c-bec8-7301669ade2b · inbound

Tight Sample Complexity of Transformers cites this paper.

Tight Sample Complexity of Transformers Auto-Regressive Next-Token Predictors are Universal Learners

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-07-02T23:57:29.162076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 3d6c804b-ca24-4ec5-b231-b2d8c0e290a6 · inbound

When Does In-Context Search Help? A Sampling-Complexity Theory of Reflection-Driven Reasoning cites this paper.

When Does In-Context Search Help? A Sampling-Complexity Theory of Reflection-Driven Reasoning Auto-Regressive Next-Token Predictors are Universal Learners

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-07-10T22:47:36.921943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation 2833c456-4f0f-4b38-919a-b17d2bf6f33b · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization Auto-Regressive Next-Token Predictors are Universal Learners

Reference 160

Resolution: unresolved; no resolver link, observed 2026-08-01T20:54:17.295148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.