Paper Citation Record · LEDGER

Language Models Can Teach Themselves to Program Better

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2207.14502.

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

pith.paper-citation-record.v1
2207.14502 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:42:20.701627Z

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

17
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 b2eff935-6c81-4569-8a00-c7568261dc0c · 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 Language Models Can Teach Themselves to Program Better

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T17:34:43.013796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3cab5184-fbff-44d3-9e5b-463591d5f182 · inbound

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models cites this paper.

Sycophancy to Subterfuge: Investigating Reward-Tampering in Large Language Models Language Models Can Teach Themselves to Program Better

Reference 167

Resolution: verified exact; arxiv_id, observed 2026-05-17T14:43:29.968662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 847ce3b9-feb4-4cd0-a4e1-5e1dec089b77 · inbound

LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers cites this paper.

LLM-FE: Automated Feature Engineering for Tabular Data with LLMs as Evolutionary Optimizers Language Models Can Teach Themselves to Program Better

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-22T23:37:15.442000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation c426333e-9b75-4b5c-a45c-5060769e203c · inbound

Self-Reasoning Language Models: Unfold Hidden Reasoning Chains with Few Reasoning Catalyst cites this paper.

Self-Reasoning Language Models: Unfold Hidden Reasoning Chains with Few Reasoning Catalyst Language Models Can Teach Themselves to Program Better

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T15:42:20.701627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6d762963-93fb-4242-8404-c3ddda46c303 · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey Language Models Can Teach Themselves to Program Better

Reference 85

Resolution: unresolved; no resolver link, observed 2026-08-07T14:11:56.444562Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 381dc394-0dfa-4d4a-9df4-36bc6f7ef19e · inbound

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing cites this paper.

Dr. Boot: Bootstrapping Program Synthesis Language Models to Perform Repairing Language Models Can Teach Themselves to Program Better

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T15:52:20.388469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16e4a717-7845-47c8-b931-7bb989f39dba · inbound

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models cites this paper.

AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models Language Models Can Teach Themselves to Program Better

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-05T15:17:13.766596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59b5718b-efb7-471c-9714-f0fbecb81711 · inbound

PseudoBridge: Pseudo Code as the Bridge for Better Semantic and Logic Alignment in Code Retrieval cites this paper.

PseudoBridge: Pseudo Code as the Bridge for Better Semantic and Logic Alignment in Code Retrieval Language Models Can Teach Themselves to Program Better

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-05-21T22:44:24.486909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5eb82c88-9520-48ad-8b34-357ce25f90e7 · inbound

FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data cites this paper.

FELA: A Multi-Agent Evolutionary System for Feature Engineering of Industrial Event Log Data Language Models Can Teach Themselves to Program Better

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:02:23.225114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation fc99723c-829b-422a-ad88-ffcdd6fd6c1d · inbound

Toward Training Superintelligent Software Agents through Self-Play SWE-RL cites this paper.

Toward Training Superintelligent Software Agents through Self-Play SWE-RL Language Models Can Teach Themselves to Program Better

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-21T16:10:20.175009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 9b3abc1f-65cb-4e1b-86f7-ce97977dab87 · inbound

Toward Training Superintelligent Software Agents through Self-Play SWE-RL cites this paper.

Toward Training Superintelligent Software Agents through Self-Play SWE-RL Language Models Can Teach Themselves to Program Better

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-03T15:02:11.344204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad03b291-1472-4102-a305-9b565fdbc09d · inbound

DecompRL: Solving Harder Problems by Learning Modular Code Generation cites this paper.

DecompRL: Solving Harder Problems by Learning Modular Code Generation Language Models Can Teach Themselves to Program Better

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-07-03T16:38:39.781703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.