Paper Citation Record · LEDGER

Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2406.12146.

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

pith.paper-citation-record.v1
2406.12146 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:57:22.088513Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:46:37.078741Z

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 fbe7f28d-5e17-4f10-9b44-c22702fbd875 · inbound

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards cites this paper.

A Blueprint for AI-Driven Software Quality: Integrating LLMs with Established Standards Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models

Reference 135

Resolution: verified exact; arxiv_id, observed 2026-05-22T13:46:37.082679Z

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 a4cf8450-6b35-482e-bce8-1995e1338d68 · inbound

CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking cites this paper.

CETBench: A Novel Dataset constructed via Transformations over Programs for Benchmarking LLMs for Code-Equivalence Checking Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-07T10:57:22.088513Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d717d99e-8e17-4e16-93c8-aaa5045b0c37 · inbound

Accelerating Latency-Critical Applications with AI-Powered Semi-Automatic Fine-Grained Parallelization on SMT Processors cites this paper.

Accelerating Latency-Critical Applications with AI-Powered Semi-Automatic Fine-Grained Parallelization on SMT Processors Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-05T13:12:44.187916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a18fbc48-b4b3-4956-a603-9faeb4fcec1d · inbound

PerfCoder: Large Language Models for Interpretable Code Performance Optimization cites this paper.

PerfCoder: Large Language Models for Interpretable Code Performance Optimization Should AI Optimize Your Code? A Comparative Study of Classical Optimizing Compilers Versus Current Large Language Models

Reference 33

Resolution: verified exact; arxiv_id, observed 2026-05-16T22:43:38.193503Z

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.