Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
As of 24 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.09662.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-23T01:59:18.546405Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T02:02:23.015725Z
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 5f155351-b94b-49a1-81a6-948943ee48c7 · inbound
CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs cites this paper.
CODEPROMPTZIP: Code-specific Prompt Compression for Retrieval-Augmented Generation in Coding Tasks with LMs Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T02:02:23.021570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c0b4d6f3-d829-40e7-9fae-6dcdfe377485 · inbound
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention cites this paper.
EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T20:56:51.773644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 23740806-5f28-4893-850b-ae44c9c8ae9c · inbound
SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair cites this paper.
SynthFix: Adaptive Neuro-Symbolic Code Vulnerability Repair Evaluating the Effectiveness and Efficiency of Demonstration Retrievers in RAG for Coding Tasks
Reference 29
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T06:41:36.545871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.