Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On Efficient and Statistical Quality Estimation for Data Annotation
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.11919.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-23T03:56:18.703995Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T03:57:29.670245Z
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 68c76a28-b268-42db-b67b-62768c398123 · inbound
How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators cites this paper.
How Humans Help LLMs: Assessing and Incentivizing Human Preference Annotators On Efficient and Statistical Quality Estimation for Data Annotation
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T03:57:29.673678Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0b6fb9b6-8fa9-4fc3-a597-425acb221fdd · inbound
Incentivizing High-Quality Human Annotations with Golden Questions cites this paper.
Incentivizing High-Quality Human Annotations with Golden Questions On Efficient and Statistical Quality Estimation for Data Annotation
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T13:42:19.364560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cca4f4e7-987b-409d-829a-e4469621fa93 · inbound
Users as Annotators: LLM Preference Learning from Comparison Mode cites this paper.
Users as Annotators: LLM Preference Learning from Comparison Mode On Efficient and Statistical Quality Estimation for Data Annotation
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T08:21:06.997533Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.