Paper Citation Record · LEDGER

Transformers Provably Solve Parity Efficiently with Chain of Thought

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2410.08633.

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

pith.paper-citation-record.v1
2410.08633 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:11:54.462324Z

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

0
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 ef7b5b22-72aa-4beb-a331-eb51b3ce4e25 · inbound

On the Emergence of Implicit Curriculum in RLVR Learning Dynamics cites this paper.

On the Emergence of Implicit Curriculum in RLVR Learning Dynamics Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-02T23:11:54.462324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc5a69b5-2553-4fb8-bd71-9f739f2bdc06 · inbound

The Power of Power Law: Asymmetry Enables Compositional Reasoning cites this paper.

The Power of Power Law: Asymmetry Enables Compositional Reasoning Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:31:08.235090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 309d9737-4ca8-40b9-936c-65dd0430c10a · inbound

The Power of Power Law: Asymmetry Enables Compositional Reasoning cites this paper.

The Power of Power Law: Asymmetry Enables Compositional Reasoning Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 30

Resolution: unresolved; no resolver link, observed 2026-07-12T18:26:05.728364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e7bb8b7-8911-4419-a4cf-5553b441b1e2 · inbound

Learning to Think from Multiple Thinkers cites this paper.

Learning to Think from Multiple Thinkers Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:56:10.679647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 46afb2d4-fd10-401b-8945-4c748efa40c2 · 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 Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:58.591059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b21e1c4a-dd87-4bde-bdd1-3a38f86547f5 · inbound

Transformers Provably Learn to Internalize Chain-of-Thought cites this paper.

Transformers Provably Learn to Internalize Chain-of-Thought Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:30.608253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 669df209-6638-45a9-8514-ef59b29132a0 · inbound

Agentic Transformers Provably Learn to Search via Reinforcement Learning cites this paper.

Agentic Transformers Provably Learn to Search via Reinforcement Learning Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 31

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T23:42:49.908741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f58d5fc5-fedc-4321-a2b9-bf18c2a9f70b · inbound

Learning through Internalization cites this paper.

Learning through Internalization Transformers Provably Solve Parity Efficiently with Chain of Thought

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-26T17:49:40.652802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.