Paper Citation Record · LEDGER

ZeroGen: Efficient Zero-shot Learning via Dataset Generation

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2202.07922.

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

pith.paper-citation-record.v1
2202.07922 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 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 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:10:19.391259Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T04:55:03.786680Z

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 68942125-6705-4a98-ab00-7eb32e504af7 · inbound

CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs cites this paper.

CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-12T21:36:46.438300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cd935fb-3de3-480b-86e7-c8b93c6734ec · inbound

ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data? cites this paper.

ToxiLab: How Well Do Open-Source LLMs Generate Synthetic Toxicity Data? ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-12T18:50:44.254968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation deb3d76c-fa16-4896-8a24-15adf0a99d8d · inbound

Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring cites this paper.

Improving Multimodal LLMs Ability In Geometry Problem Solving, Reasoning, And Multistep Scoring ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-12T04:59:45.120907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85e47239-faa0-4d04-8bc9-bfd99af6273d · inbound

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 222

Resolution: unresolved; no resolver link, observed 2026-08-11T22:57:02.120043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dcc5eaf-4c49-46da-b656-b0dbfaeca161 · inbound

Measuring Diversity in Synthetic Datasets cites this paper.

Measuring Diversity in Synthetic Datasets ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-08T04:54:50.944354Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ff7a3f5-da61-4a59-8b5d-643146f02965 · inbound

Improving Automated Secure Code Reviews: A Synthetic Dataset for Code Vulnerability Flaws cites this paper.

Improving Automated Secure Code Reviews: A Synthetic Dataset for Code Vulnerability Flaws ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:10:19.391259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 447994e4-bca2-45d1-99e4-4788cf74e38a · inbound

Synthline: A Product Line Approach for Synthetic Requirements Engineering Data Generation using Large Language Models cites this paper.

Synthline: A Product Line Approach for Synthetic Requirements Engineering Data Generation using Large Language Models ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T23:59:12.408190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d3c46d2-027f-47ac-8757-7cd61c6761b9 · inbound

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning cites this paper.

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-06T23:12:19.041283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c8fafe02-40b5-4d94-884c-ece5fae8a87b · inbound

Few-Shot Inspired Generative Zero-Shot Learning cites this paper.

Few-Shot Inspired Generative Zero-Shot Learning ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T19:49:57.476204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae640134-eb79-4a5e-8f8f-1a948690d58b · inbound

Large Language Model for Extracting Complex Contract Information in Industrial Scenes cites this paper.

Large Language Model for Extracting Complex Contract Information in Industrial Scenes ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T19:05:00.516123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30e50ffc-9452-48bb-ac5d-c14f7fac065b · inbound

Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals cites this paper.

Evaluating LLMs Without Oracle Feedback: Agentic Annotation Evaluation Through Unsupervised Consistency Signals ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T20:11:41.698533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6194b3da-9659-41e4-9142-b09eed3d4836 · inbound

Agents of Diffusion: Enhancing Diffusion Language Models with Multi-Agent Reinforcement Learning for Structured Data Generation (Extended Version) cites this paper.

Agents of Diffusion: Enhancing Diffusion Language Models with Multi-Agent Reinforcement Learning for Structured Data Generation (Extended Version) ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-03T11:14:51.788738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95dac23a-f6ab-46e1-98a6-cc57fed5a0c5 · 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 ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:28:17.086217Z

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 f00e19bc-3194-4bf3-b79c-5796b3d104c6 · inbound

BOOKMARKS: Efficient Active Storyline Memory for Role-playing cites this paper.

BOOKMARKS: Efficient Active Storyline Memory for Role-playing ZeroGen: Efficient Zero-shot Learning via Dataset Generation

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-15T04:55:03.790255Z

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.