Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:47:56.931143Z

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 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.