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Paper Citation Record · LEDGER

Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.13588.

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

pith.paper-citation-record.v1
2403.13588 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 2026-08-21T06:32:19.484+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:40:43.432268Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T15:14:16.383423Z

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 3943eb3b-19a8-4960-8e7c-1dc35e61840b · inbound

Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications cites this paper.

Evolutionary Computation and Large Language Models: A Survey of Methods, Synergies, and Applications Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models

Reference 38

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:14:16.389284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-07T15:14:07.946058Z digest=sha256:c9a726f81bbbdec0502c177f62e682c57fcfb634a65459ce15ea838834561f57

Observation 3addee72-4e84-4ccb-8aef-8a138ba2a22f · inbound

LLM-based Multi-Agent System for Intelligent Refactoring of Haskell Code cites this paper.

LLM-based Multi-Agent System for Intelligent Refactoring of Haskell Code Genetic Auto-prompt Learning for Pre-trained Code Intelligence Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-15T18:40:43.432268Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:40:43.432268Z digest=sha256:23e9ee6dc2c99c7a6b01e53acfda3a92c0e501dd12f8501c05ed28a96259fdb8