Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:1810.10147.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T21:56:31.570576Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T11:01:21.019258Z
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 31ef4330-b3ef-426a-946f-de3e6960b8b3 · inbound
GLiREL -- Generalist Model for Zero-Shot Relation Extraction cites this paper.
GLiREL -- Generalist Model for Zero-Shot Relation Extraction FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T21:56:31.570576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 897b0e9f-4ec2-42d3-ad53-81c119e8f2a5 · inbound
Learning Mechanism Underlying NLP Pre-Training and Fine-Tuning cites this paper.
Learning Mechanism Underlying NLP Pre-Training and Fine-Tuning FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T11:01:21.031563Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 8d39323f-e64d-429f-abf4-1048cb2d4f7d · inbound
Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals cites this paper.
Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals FewRel: A Large-Scale Supervised Few-Shot Relation Classification Dataset with State-of-the-Art Evaluation
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T20:11:41.618338Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.