Paper Citation Record · LEDGER

Code Pretraining Improves Entity Tracking Abilities of Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2405.21068.

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

pith.paper-citation-record.v1
2405.21068 v1

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 2026-08-07T06:34:17.273281+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T05:00:56.434793Z

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

1
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 1aac1ced-65ba-4c98-bf37-e0020b7023b3 · inbound

RExBench: Can coding agents autonomously implement AI research extensions? cites this paper.

RExBench: Can coding agents autonomously implement AI research extensions? Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-19T07:37:08.889606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 829a7b52-5cb7-4eeb-a162-444585bc8d93 · inbound

Can Large Language Models Generalize Procedures Across Representations? cites this paper.

Can Large Language Models Generalize Procedures Across Representations? Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-03T05:00:56.434793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18130f3b-bec1-4c53-b021-4569ac040af8 · inbound

Brain Score Tracks Shared Properties of Languages: Evidence from Many Natural Languages and Structured Sequences cites this paper.

Brain Score Tracks Shared Properties of Languages: Evidence from Many Natural Languages and Structured Sequences Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:05:08.272109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e1d2c80c-6822-40c8-b071-8c0649e70b69 · inbound

Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appear cites this paper.

Not-So-Strange Love: Language Models and Generative Linguistic Theories are More Compatible than They Appear Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:21:16.841059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a4824bea-7371-4ecd-affd-9919f25b3137 · inbound

A retrieval conditioned rebinding circuit for dynamic entity tracking in large language models cites this paper.

A retrieval conditioned rebinding circuit for dynamic entity tracking in large language models Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:27:26.324213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5bd3872b-1f70-4441-a4bd-8be4750e9a19 · inbound

Natural Identifiers for Privacy and Data Audits in Large Language Models cites this paper.

Natural Identifiers for Privacy and Data Audits in Large Language Models Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 12

Resolution: verified exact; arxiv_id, observed 2026-07-04T16:49:57.324356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6bda2c34-7f17-4ab6-b47e-bf2a9e9db7f2 · inbound

Domain-Aware Scaling Laws Uncover Data Synergy cites this paper.

Domain-Aware Scaling Laws Uncover Data Synergy Code Pretraining Improves Entity Tracking Abilities of Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-07-14T07:24:27.255815Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.