Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2009.02696.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:13:27.392556Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-18T21:16:51.443655Z
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 4aae182a-f161-4ece-9ecf-f4162c7c65c6 · inbound
COBRA: A Continual Learning Approach to Vision-Brain Understanding cites this paper.
COBRA: A Continual Learning Approach to Vision-Brain Understanding SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
Reference 79
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:53:48.813106Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ed53cd99-55b6-4565-80a1-0271c8a36396 · inbound
Are Large Language Models Good at Detecting Propaganda? cites this paper.
Are Large Language Models Good at Detecting Propaganda? SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:13:27.392556Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53526175-b3d3-41a4-b77b-8f231c3abdec · inbound
Hybrid Annotation for Propaganda Detection: Integrating LLM Pre-Annotations with Human Intelligence cites this paper.
Hybrid Annotation for Propaganda Detection: Integrating LLM Pre-Annotations with Human Intelligence SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T18:19:18.661041Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ae4e6bc-0e39-41de-8b9c-f52338de6926 · inbound
BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding cites this paper.
BRAIN: Bias-Mitigation Continual Learning Approach to Vision-Brain Understanding SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
Reference 125
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T21:16:51.446486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 212f56e3-d7cf-410f-8970-388ab90bf74d · inbound
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas cites this paper.
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas SemEval-2020 Task 11: Detection of Propaganda Techniques in News Articles
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T19:47:53.799174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.