Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code
As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2308.13507.
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 2026-08-21T06:32:19.484+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T00:38:49.591625Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T08:47:49.727672Z
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 b01b3728-3e00-445a-ba21-fb997e840141 · inbound
Learning to Ask: When LLM Agents Meet Unclear Instruction cites this paper.
Learning to Ask: When LLM Agents Meet Unclear Instruction Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T21:13:28.069470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation 0bb63dac-7b92-40fd-a896-faf9ec1a610b · inbound
Guiding Human Validation of LLM-Generated Code via Verifiable Literate Programming cites this paper.
Guiding Human Validation of LLM-Generated Code via Verifiable Literate Programming Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T08:47:49.729174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.
Observation d03e738a-100c-4c92-bf6e-7bbe0685bf18 · inbound
CLAIM: Leading Open-domain Active Clarification of Large Language Models with Uncertainty Measurement cites this paper.
CLAIM: Leading Open-domain Active Clarification of Large Language Models with Uncertainty Measurement Large Language Models Should Ask Clarifying Questions to Increase Confidence in Generated Code
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T00:38:49.591625Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.