Paper Citation Record · LEDGER

SarcasmBench: Towards Evaluating Large Language Models on Sarcasm Understanding

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2408.11319.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2408.11319 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:06:09.431496Z

measured 0 of 1 external citation measurements

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 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 2026-08-07T06:34:17.273281+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.