Paper Citation Record · LEDGER

Large language models for aspect-based sentiment analysis

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2310.18025.

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

pith.paper-citation-record.v1
2310.18025 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:00:54.612111Z

measured 1 of 1 external citation measurements

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

12
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 7928d9a0-0cb4-46b8-95c8-15b24bb28c80 · inbound

Evaluating Zero-Shot Multilingual Aspect-Based Sentiment Analysis with Large Language Models cites this paper.

Evaluating Zero-Shot Multilingual Aspect-Based Sentiment Analysis with Large Language Models Large language models for aspect-based sentiment analysis

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T14:00:54.612111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a6d4191-c7b0-496f-b1ef-75be36cb66ad · inbound

DS$^2$-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis cites this paper.

DS$^2$-ABSA: Dual-Stream Data Synthesis with Label Refinement for Few-Shot Aspect-Based Sentiment Analysis Large language models for aspect-based sentiment analysis

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-11T11:54:28.612603Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abd5645c-d709-4412-a99f-4655acf23a74 · inbound

Large Language Models Enhanced by Plug and Play Syntactic Knowledge for Aspect-based Sentiment Analysis cites this paper.

Large Language Models Enhanced by Plug and Play Syntactic Knowledge for Aspect-based Sentiment Analysis Large language models for aspect-based sentiment analysis

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-07T00:43:06.571149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84452df3-3955-4398-bdef-d010013870ac · inbound

Balanced Training Data Augmentation for Aspect-Based Sentiment Analysis cites this paper.

Balanced Training Data Augmentation for Aspect-Based Sentiment Analysis Large language models for aspect-based sentiment analysis

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T17:59:27.544863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb7ee6b9-951a-41c3-9951-547f32398b0d · inbound

Cross-lingual Aspect-Based Sentiment Analysis: A Survey on Tasks, Approaches, and Challenges cites this paper.

Cross-lingual Aspect-Based Sentiment Analysis: A Survey on Tasks, Approaches, and Challenges Large language models for aspect-based sentiment analysis

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-05T21:03:14.912695Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e312806-f204-44ec-9142-6fe8830f133c · inbound

LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset cites this paper.

LASQ: A Low-resource Aspect-based Sentiment Quadruple Extraction Dataset Large language models for aspect-based sentiment analysis

Reference 49

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T08:40:58.992873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0fc09e4b-2455-4f9c-939a-f87bd05db5ca · 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 Large language models for aspect-based sentiment analysis

Reference 64

Resolution: verified exact; arxiv_id, observed 2026-05-09T05:20:11.659332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e633d9d8-3c06-4c03-bdad-a167355e4b77 · inbound

Single-Pass, Depth-Selective Reading for Multi-Aspect Sentiment Analysis cites this paper.

Single-Pass, Depth-Selective Reading for Multi-Aspect Sentiment Analysis Large language models for aspect-based sentiment analysis

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:33:58.141196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.