Paper Citation Record · LEDGER

Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2306.15766.

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

pith.paper-citation-record.v1
2306.15766 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 2026-08-11T15:05:32.416131Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-06-30T18:04:57.847704Z

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 ffa97894-b970-462f-a70c-6e359745a0ea · inbound

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences cites this paper.

Can AI Extract Antecedent Factors of Human Trust in AI? An Application of Information Extraction for Scientific Literature in Behavioural and Computer Sciences Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T15:05:32.416131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c3996ed-e992-4e08-a607-64a6215be73c · inbound

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing cites this paper.

Contrastive Learning on LLM Back Generation Treebank for Cross-domain Constituency Parsing Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T13:47:56.931143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 906048ec-31ac-4b90-8269-a8d2f54c5d0f · inbound

Revisiting Active Learning under (Human) Label Variation cites this paper.

Revisiting Active Learning under (Human) Label Variation Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:29:48.897833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38d4b28d-df35-432e-81cf-cd38db92d4b3 · inbound

QUEST: Query Optimization in Unstructured Document Analysis cites this paper.

QUEST: Query Optimization in Unstructured Document Analysis Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T19:10:17.552249Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6214ee55-0263-40dd-8ada-baa598cc5a41 · inbound

ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection cites this paper.

ACD-CLIP: Decoupling Representation and Dynamic Fusion for Zero-Shot Anomaly Detection Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T21:53:04.275918Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb27085f-bb3b-4086-a198-57b7f2157896 · inbound

Evaluating Large Language Models as Expert Annotators cites this paper.

Evaluating Large Language Models as Expert Annotators Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T21:57:59.306767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d220476c-97bb-4dc4-abec-902b8ada76a8 · inbound

Occupational Prompting Reveals Cultural Bias in Large Language Models cites this paper.

Occupational Prompting Reveals Cultural Bias in Large Language Models Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-06-30T18:04:57.849425Z

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 491c8602-229d-41b0-b950-fcba7369e9b3 · inbound

Labeling Training Data for Entity Matching Using Large Language Models cites this paper.

Labeling Training Data for Entity Matching Using Large Language Models Large Language Models as Annotators: Enhancing Generalization of NLP Models at Minimal Cost

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-06-30T12:54:40.392509Z

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.