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Paper Citation Record · LEDGER

Python Symbolic Execution with LLM-powered Code Generation

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2409.09271.

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

pith.paper-citation-record.v1
2409.09271 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 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:34:01.107321Z

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 cdc3fd9c-bde4-4a69-9dff-47532bd72e59 · inbound

A Contemporary Survey of Large Language Model Assisted Program Analysis cites this paper.

A Contemporary Survey of Large Language Model Assisted Program Analysis Python Symbolic Execution with LLM-powered Code Generation

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-09T05:32:24.190024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:32:24.190024Z digest=sha256:61045d144c489d20c15f12b072e80705f4efe976530894a85986fb81f0ef7c6b

Observation 10b63110-9f54-4891-857f-1c037293eae6 · inbound

Integrating Symbolic Execution into the Fine-Tuning of Code-Generating LLMs cites this paper.

Integrating Symbolic Execution into the Fine-Tuning of Code-Generating LLMs Python Symbolic Execution with LLM-powered Code Generation

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T11:34:01.107321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T11:34:01.107321Z digest=sha256:6f3acc9e84376dae61cba7c8a3811fb9a7028accf9f8c4bfb2ac46c1ec870493

Observation ac872aab-64d6-4223-bb9b-5bdc16925ea5 · inbound

Can LLMs Replace Humans During Code Chunking? cites this paper.

Can LLMs Replace Humans During Code Chunking? Python Symbolic Execution with LLM-powered Code Generation

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T23:10:14.656505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T23:10:14.656505Z digest=sha256:469b326f35be5f0c55bf236a3bfb3a5b8f264f962f47d691857cec22a95bc156

Observation 8032930b-5cd9-43ca-8ac9-6124b50f5a7e · inbound

Can Large Language Models Reason About Complex Execution Paths? An Empirical Study on Python cites this paper.

Can Large Language Models Reason About Complex Execution Paths? An Empirical Study on Python Python Symbolic Execution with LLM-powered Code Generation

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-03T20:51:08.346652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T20:51:08.346652Z digest=sha256:a34f4323b2b133658ab808a16cfa492726bcfada8a2d059975886086df33336e

Observation f4d909c0-b32d-459e-813f-b8f494cca4fe · inbound

A Neuro-Symbolic Framework for Accountability in Public-Sector AI cites this paper.

A Neuro-Symbolic Framework for Accountability in Public-Sector AI Python Symbolic Execution with LLM-powered Code Generation

Reference 90

Resolution
verified exact
arxiv_id, observed 2026-05-16T23:28:40.993296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-16T23:24:56.685420Z digest=sha256:e78e891d7eb971f030c51679970504c596ccb9daf111be7c2ac710ea58ee8086

Observation 064d76ea-ca15-4fc0-9137-0fbdb91452b0 · inbound

ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing cites this paper.

ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing Python Symbolic Execution with LLM-powered Code Generation

Reference 31

Resolution
metadata mismatch
arxiv_id, observed 2026-06-26T05:09:00.761389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T04:30:51.720496Z digest=sha256:f05254d7ee8ed71f49b5e8295038fcbc881d0b3ebf5f25326dd8fa37dddeba4b

Observation 6422d228-54ab-4031-bddf-6200b2dd5d2c · inbound

Guiding Human Validation of LLM-Generated Code via Verifiable Literate Programming cites this paper.

Guiding Human Validation of LLM-Generated Code via Verifiable Literate Programming Python Symbolic Execution with LLM-powered Code Generation

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-07-03T08:47:49.669884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-07-03T08:42:04.804042Z digest=sha256:8cb136bb99fee570fcec6b2c5f9b2f0acafd08c3954b459caebfc29a37ec685c