Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach
As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.10398.
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 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:17:35.355796Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-11T01:04:03.697423Z
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 8b65d380-44ba-4d29-8582-1a4e1e7ec806 · 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 Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-08-11T01:04:03.704852Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation bb7e18b3-44b6-493d-ba92-d64f2de6393a · inbound
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency cites this paper.
Optimizing Token Consumption in LLMs: A Nano Surge Approach for Code Reasoning Efficiency Prompt Learning for Multi-Label Code Smell Detection: A Promising Approach
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:17:35.355796Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.