Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2304.07575.
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 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:18:30.683999Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T04:43:53.920592Z
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 e0095778-ee88-43ec-ba91-bd4943fcc015 · inbound
Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models cites this paper.
Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T04:43:53.922796Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.
Observation 008db99e-45c3-4c8f-9c42-2087bee60e20 · inbound
Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering cites this paper.
Instruct or Interact? Exploring and Eliciting LLMs' Capability in Code Snippet Adaptation Through Prompt Engineering What Makes Good In-context Demonstrations for Code Intelligence Tasks with LLMs?
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:18:30.683999Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.