Paper Citation Record · LEDGER

On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.14197.

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

pith.paper-citation-record.v1
2406.14197 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:59:01.413100Z

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 827930a6-480e-4f74-a00f-9c5b92afd942 · inbound

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation cites this paper.

Chain-of-Thought in Large Language Models: Decoding, Projection, and Activation On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T21:59:01.413100Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e38e12c0-58f9-4708-be68-528a4e072062 · inbound

Are Latent Reasoning Models Easily Interpretable? cites this paper.

Are Latent Reasoning Models Easily Interpretable? On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T19:45:44.904686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e6ef6b7-06c3-4c4d-bca4-0ae03c4c1bdc · inbound

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete cites this paper.

Rethinking the Role of Positional Encoding: Sliding-Window Transformers without PE Remain Turing Complete On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T22:06:16.195209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation c5ecfe0e-39fb-4b02-9252-f143e068b3ea · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization On the Representational Capacity of Neural Language Models with Chain-of-Thought Reasoning

Reference 79

Resolution: unresolved; no resolver link, observed 2026-08-01T20:54:09.875107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.