Paper Citation Record · LEDGER

Want To Reduce Labeling Cost? GPT-3 Can Help

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2108.13487.

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

pith.paper-citation-record.v1
2108.13487 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:05:26.111410Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-10T06:15:00.866473Z

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 36c84df1-2c27-4fa1-9f92-4c2f9c18ef8e · inbound

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes cites this paper.

Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 105

Resolution: verified exact; arxiv_id, observed 2026-05-21T20:50:09.491792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation bd00ac67-0234-436c-bc48-85a4bd9e4071 · inbound

DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization cites this paper.

DocSum: Domain-Adaptive Pre-training for Document Abstractive Summarization Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T18:09:17.183781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5c85787-fc21-44b3-9fca-fcf7d1967f96 · inbound

The Impostor is Among Us: Can Large Language Models Capture the Complexity of Human Personas? cites this paper.

The Impostor is Among Us: Can Large Language Models Capture the Complexity of Human Personas? Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-10T21:35:14.218552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56ad614d-ed40-4e59-8cef-8739f5b59575 · inbound

A Comprehensive Survey of Synthetic Tabular Data Generation cites this paper.

A Comprehensive Survey of Synthetic Tabular Data Generation Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:05:26.111410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbd9f76a-b537-475f-aaa8-953c52615def · inbound

Learning to Select Visual In-Context Demonstrations cites this paper.

Learning to Select Visual In-Context Demonstrations Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T05:46:07.977425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c4ec150-3c55-46ef-bf94-415ec4f87faa · inbound

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation cites this paper.

Structured Exploration and Exploitation of Label Functions for Automated Data Annotation Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:28:17.099275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 8338bf30-bed1-4042-aff7-27c7c74e3a89 · inbound

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection cites this paper.

Dynamic Emotion and Personality Profiling for Multimodal Deception Detection Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:31:30.971806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c5f0c842-2204-4096-ae3f-eb53c06204ab · inbound

Refining and Reusing Annotation Guidelines for LLM Annotation cites this paper.

Refining and Reusing Annotation Guidelines for LLM Annotation Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-21T05:13:58.635613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation fadce774-5685-4df2-9812-8d797d1c0b50 · inbound

Human agency in initial human-AI proof formalization workflows cites this paper.

Human agency in initial human-AI proof formalization workflows Want To Reduce Labeling Cost? GPT-3 Can Help

Reference 255

Resolution: verified exact; arxiv_id, observed 2026-06-28T09:31:48.850172Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.