Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Rethinking Negative Instances for Generative Named Entity Recognition
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2402.16602.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-30T17:59:31.336429Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T08:48:01.865660Z
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 2766f3ff-4762-4d4f-b7e1-fe6a54b7065c · inbound
DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition cites this paper.
DiZiNER: Disagreement-guided Instruction Refinement via Pilot Annotation Simulation for Zero-shot Named Entity Recognition Rethinking Negative Instances for Generative Named Entity Recognition
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T08:48:01.867882Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation dc47ee55-1d74-41b9-8dcd-127695ce0d3b · inbound
DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models cites this paper.
DIRECT: Direct Decoding for Efficient and Aligned Sequence Labeling with Large Language Models Rethinking Negative Instances for Generative Named Entity Recognition
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T17:59:31.336429Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.