Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2412.02279.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-10T16:34:01.296047Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 32d07096-abe4-47e2-9ffa-2348db53a8a9 · inbound
LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset cites this paper.
LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T08:40:58.973056Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b17fe7a7-2618-4cde-b459-c1100c91df63 · inbound
Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model cites this paper.
Annotation Quality in Aspect-Based Sentiment Analysis: A Case Study Comparing Experts, Students, Crowdworkers, and Large Language Model A Comprehensive Evaluation of Large Language Models on Aspect-Based Sentiment Analysis
Reference 91
- Resolution
- verified exact
- arxiv_id, observed 2026-05-09T05:20:11.716528Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.