Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.16416.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:30:43.704737Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-13T20:13:13.164813Z
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 25c25e3a-7ab5-4e77-957f-277fca33f16d · inbound
AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length cites this paper.
AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T04:30:43.704737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f524e44d-300f-4f18-a758-8233281c7d38 · inbound
Evaluating the Environmental Impact of using SLMs and Prompt Engineering for Code Generation cites this paper.
Evaluating the Environmental Impact of using SLMs and Prompt Engineering for Code Generation Selection of Prompt Engineering Techniques for Code Generation through Predicting Code Complexity
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T20:13:13.167195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.