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Paper Citation Record · LEDGER

Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.12806.

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

pith.paper-citation-record.v1
2406.12806 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T19:24:00.042254Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T13:46:37.085152Z

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 0f9f0a3a-5694-4348-94d2-f882f32775c1 · inbound

Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews cites this paper.

Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-08T19:24:00.042254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T19:24:00.042254Z digest=sha256:429d282867f24500395d31442fa8f5dfa9fdcad6c92e938633c64a8fb5457895

Observation fc21f34e-1693-4da9-9dbe-26e7048f9768 · 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 Identifying Performance-Sensitive Configurations in Software Systems through Code Analysis with LLM Agents

Reference 92

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:46:37.088472Z

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.

source=pdf_text observed=2026-05-22T13:45:28.789452Z digest=sha256:6bd4132259cab2c59f0a2464b95859ac265e3a24d308a3f699f228f0db97ddc2