Pith. sign in

Paper Citation Record · LEDGER

Code Execution with Pre-trained Language Models

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2305.05383.

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

pith.paper-citation-record.v1
2305.05383 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 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 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T23:21:56.471608Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T02:33:32.382558Z

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 b4f4e3df-3650-4d3a-8592-4782c91c23d8 · inbound

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution cites this paper.

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution Code Execution with Pre-trained Language Models

Reference 4

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T20:57:16.372435Z

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.

source=pdf_text observed=2026-05-14T20:57:16.327963Z digest=sha256:922f963ddce607228b8debb705fb467a79d08d893681349b1a742c08eb47129c

Observation cd356773-04dc-47ff-9bd9-d19605d6259a · 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 Code Execution with Pre-trained Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-10T17:34:42.997311Z

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.

source=arxiv_source observed=2026-05-10T17:34:42.565806Z digest=sha256:0dc06f949ee9aa894c8528980b30aa9b89d6453b250f17994807af6f77211a42

Observation d7b3f050-dbff-483e-a258-9dcf214bf9de · inbound

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models cites this paper.

A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models Code Execution with Pre-trained Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-09T23:21:56.471608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T23:21:56.471608Z digest=sha256:39148114e2eaee7e84ac8a2346856aa341903d4f4d476fe3c56de6bdbd1625a2

Observation c4b0de17-198b-4866-8fdc-3c66a8dd9ae7 · inbound

Code Simulation as a Proxy for High-order Tasks in Large Language Models cites this paper.

Code Simulation as a Proxy for High-order Tasks in Large Language Models Code Execution with Pre-trained Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-09T04:32:42.487463Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T04:32:42.487463Z digest=sha256:de351b158b51d481e774cd34773ee1a8c19ee723392c2e91b93bbe9aaf09d6dc

Observation a6e2de93-8efb-4580-b8d1-f3583059b8dc · inbound

SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis cites this paper.

SV-TrustEval-C: Evaluating Structure and Semantic Reasoning in Large Language Models for Source Code Vulnerability Analysis Code Execution with Pre-trained Language Models

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-07T13:55:18.438148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:55:18.438148Z digest=sha256:c8cd9ed08a12b00a2cd1ac70e09fe6b06ea7e269ba100dcf3eb27ca745c43ead

Observation 391b40e4-5565-48cf-9bc7-65d7aea0051b · inbound

CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning cites this paper.

CodeReasoner: Enhancing the Code Reasoning Ability with Reinforcement Learning Code Execution with Pre-trained Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T14:50:27.943038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:50:27.943038Z digest=sha256:e78585158509d727cb10e758cefe0293bde09705d56f373750d28d5c8c55862b

Observation ef5ff00b-223a-4a75-aaa9-6a0e4c8241df · inbound

Training Transformers as a Universal Computer cites this paper.

Training Transformers as a Universal Computer Code Execution with Pre-trained Language Models

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-11T23:36:38.736344Z

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.

source=pdf_text observed=2026-05-07T16:36:19.729400Z digest=sha256:a83701f373f780e9d78b8b73783aa8dada45bb316a84eb07c9cacb5d8776a34f

Observation 2575dd0d-d269-40da-8914-6c612ebb7db8 · inbound

Teaching LLMs Program Semantics via Symbolic Execution Traces cites this paper.

Teaching LLMs Program Semantics via Symbolic Execution Traces Code Execution with Pre-trained Language Models

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:26:13.086299Z

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.

source=pdf_text observed=2026-05-08T08:56:25.022619Z digest=sha256:2be55105e4f76e2d411aa7afadc0342c7d629ade539fe5c5b3a21627d54ef630

Observation e05c8a5f-8747-44ca-be04-62ea404a95e6 · inbound

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning cites this paper.

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning Code Execution with Pre-trained Language Models

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:32:20.192915Z

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.

source=arxiv_source observed=2026-05-13T05:27:37.521421Z digest=sha256:dc28e95981ea00362a25565808cda7f52d33ef750ce74faa5c7006536a561365

Observation 2fdbb378-c33f-4ef4-8d34-fdcdfa649175 · inbound

SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades cites this paper.

SWE-Chain: Benchmarking Coding Agents on Chained Release-Level Package Upgrades Code Execution with Pre-trained Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:33:32.384438Z

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.

source=arxiv_source observed=2026-05-15T02:31:18.183715Z digest=sha256:431ccbc8337cbdeda8cfde342dacc10aad4de4f5c0721c0c2aeb1603b179c71d

Observation f4b80cde-dddb-4e7a-9ad3-78d7b5d252d8 · inbound

Hierarchical Domain Generalization cites this paper.

Hierarchical Domain Generalization Code Execution with Pre-trained Language Models

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-01T20:54:10.903870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T20:54:10.903870Z digest=sha256:1ee0dd7b0cdb8fdef235fcd0e5fb5e15431363a85e63ab64f9c8150c6deeef42