Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2408.11319.
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 2026-08-14T06:32:32.682623+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T22:51:15.648412Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T11:32:17.533475Z
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 3bb74c5b-8a6f-477a-bb5c-724b6fc88807 · inbound
Pragmatic Metacognitive Prompting Improves LLM Performance on Sarcasm Detection cites this paper.
Pragmatic Metacognitive Prompting Improves LLM Performance on Sarcasm Detection SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T22:51:15.648412Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4e1bff7c-ec5c-491a-bdde-e953f2aae8f7 · inbound
Sarc7: Evaluating Sarcasm Detection and Generation with Seven Types and Emotion-Informed Techniques cites this paper.
Sarc7: Evaluating Sarcasm Detection and Generation with Seven Types and Emotion-Informed Techniques SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:06:09.431496Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 169de604-5000-432c-a759-4a9176bb8b2a · inbound
Leveraging Large Language Models for Sarcastic Speech Annotation in Sarcasm Detection cites this paper.
Leveraging Large Language Models for Sarcastic Speech Annotation in Sarcasm Detection SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T11:32:17.536418Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.
Observation 1464983c-5410-41af-baac-a34970b5ff2c · inbound
CAF-I: A Collaborative Multi-Agent Framework for Enhanced Irony Detection with Large Language Models cites this paper.
CAF-I: A Collaborative Multi-Agent Framework for Enhanced Irony Detection with Large Language Models SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:18:03.506201Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15bd0e52-85d4-4162-9cb2-5ceb46f62b70 · inbound
Spoken in Jest, Detected in Earnest: A Systematic Review of Sarcasm Recognition -- Multimodal Fusion, Challenges, and Future Prospects cites this paper.
Spoken in Jest, Detected in Earnest: A Systematic Review of Sarcasm Recognition -- Multimodal Fusion, Challenges, and Future Prospects SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding
Reference 93
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T05:59:46.055424Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.