Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2411.00865.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T11:26:57.806487Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation c771b63e-d2ec-4cc6-84e0-8e204cb6e895 · inbound
Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation cites this paper.
Optimizing Code Runtime Performance through Context-Aware Retrieval-Augmented Generation Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T11:26:57.806487Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d08cf546-4ffb-4f22-ab5b-c2fbb7745a67 · inbound
Repository-Level Solidity Code Generation with Large Language Models: From Prompting to Fine-Tuning cites this paper.
Repository-Level Solidity Code Generation with Large Language Models: From Prompting to Fine-Tuning Demo-Craft: Using In-Context Learning to Improve Code Generation in Large Language Models
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-06-26T16:49:35.661066Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.