Paper Citation Record · LEDGER

Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2406.12513.

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

pith.paper-citation-record.v1
2406.12513 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T14:00:07.873543Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T19:46:11.124564Z

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 c1e00833-c93b-4aa2-b548-6e61aa40d5f3 · inbound

How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study cites this paper.

How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T01:04:03.574583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62160b0b-7e95-4e23-88ac-17688e03975a · inbound

Correctness Assessment of Code Generated by Large Language Models Using Internal Representations cites this paper.

Correctness Assessment of Code Generated by Large Language Models Using Internal Representations Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-10T16:41:31.200937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0798830c-7e65-41b3-9ecb-5098966531e3 · inbound

SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment cites this paper.

SOK: Exploring Hallucinations and Security Risks in AI-Assisted Software Development with Insights for LLM Deployment Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-09T22:01:05.832706Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5d20c69-ad66-4d32-974f-348bf9b35759 · inbound

A Study of LLMs' Preferences for Libraries and Programming Languages cites this paper.

A Study of LLMs' Preferences for Libraries and Programming Languages Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 53

Resolution: verified exact; arxiv_id, observed 2026-05-22T22:55:12.373252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f90df8a5-b5a4-48de-811c-0bd080076f6b · inbound

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI cites this paper.

Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-07T14:15:42.284567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb79a65c-2733-46be-bfc3-35c2e7b6ecd8 · inbound

HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding cites this paper.

HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:03:33.050474Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d3eebfc-bd08-4fb8-9e8c-8713b70dc247 · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 259

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:43.279936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d458d646-49cc-48c8-886f-cd8de8ec2006 · inbound

Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions cites this paper.

Curiosity by Design: An LLM-based Coding Assistant Asking Clarification Questions Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-06T13:00:21.545266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93deb7bd-19d7-4a82-afe3-205f91a489a1 · inbound

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code cites this paper.

A Causal Perspective on Measuring, Explaining and Mitigating Smells in LLM-Generated Code Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T06:49:07.787886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6d40099-5f36-4480-b7ff-73d69ce004a0 · inbound

A Large-Scale Comprehensive Measurement of AI-Generated Code in Real-World Repositories cites this paper.

A Large-Scale Comprehensive Measurement of AI-Generated Code in Real-World Repositories Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-14T22:49:33.967874Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e60c91e3-c44c-4340-aa55-f96a438a759c · inbound

DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation cites this paper.

DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T05:40:59.433920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 217f39a2-0b0a-4769-b3eb-a4942bed2118 · inbound

R+R: Reassessing Java Security API Misuse in Current LLMs: A Replication on JCA and JSSE APIs with External Security Knowledge cites this paper.

R+R: Reassessing Java Security API Misuse in Current LLMs: A Replication on JCA and JSSE APIs with External Security Knowledge Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T19:46:11.126428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4df774f6-487a-4bf7-83d5-5580ac79a99f · inbound

Insecure Coding Preferences in Long-Term Memory: Security Risks for LLM-based Code Generation cites this paper.

Insecure Coding Preferences in Long-Term Memory: Security Risks for LLM-based Code Generation Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-01T17:31:54.928522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 500e2415-2c1f-4b80-aa7f-36e1d3560f22 · inbound

The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting cites this paper.

The Illusion of Secure LLM Code: Closing the Security Gap via Iterative Reprompting Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-07-30T15:13:30.424749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e0c634d-474c-41cf-b94a-1668979b14e3 · inbound

Do Influence Tactics Matter? Investigating Prompt Framing Effects in LLM Code Generation cites this paper.

Do Influence Tactics Matter? Investigating Prompt Framing Effects in LLM Code Generation Can We Trust Large Language Models Generated Code? A Framework for In-Context Learning, Security Patterns, and Code Evaluations Across Diverse LLMs

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T14:00:07.873543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.