Pith. sign in

Paper Citation Record · LEDGER

Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2205.12679.

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

pith.paper-citation-record.v1
2205.12679 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:20:36.478212Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T13:17:39.485879Z

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 290f3a91-3963-42fc-b09c-9f70de7d98fe · inbound

ShieldGemma: Generative AI Content Moderation Based on Gemma cites this paper.

ShieldGemma: Generative AI Content Moderation Based on Gemma Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-20T13:17:39.488263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-20T13:17:39.444002Z digest=sha256:33f87585d9acdab2d0ad70e87381deddf5fe5e9a2e297a2aaf88bcd04f27ecc9

Observation 69ff358c-c0ed-411b-8227-8e09868ec054 · inbound

Few-shot LLM Synthetic Data with Distribution Matching cites this paper.

Few-shot LLM Synthetic Data with Distribution Matching Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-08T17:20:36.478212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:20:36.478212Z digest=sha256:b7ecb23ef2185ede930bf5ec10ed2fa3f4ebb77dbd1f22dde001f09b8310f88c

Observation 5b478ff1-c744-4863-b47d-ed88d23ab3f3 · inbound

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects cites this paper.

ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialects Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:56:01.049430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:56:01.049430Z digest=sha256:6ad2db0a9eac207af1351ffcb33fd982b0a7a4633d2d7e8deb3888522329ed89

Observation 33813681-eb5d-418f-ad11-efa2fd5388e3 · inbound

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding cites this paper.

All in One: A Unified Synthetic Data Pipeline for Multimodal Video Understanding Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:31:03.933237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T15:26:55.369840Z digest=sha256:08df047a3e6dd48bd8c0b3e0ffcc38e7e45101ca73975a5eca35fd1a2247152b

Observation d2469264-f6d1-4aa5-9bff-23483fb9e404 · inbound

Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles cites this paper.

Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles Self-Guided Noise-Free Data Generation for Efficient Zero-Shot Learning

Reference 204

Resolution
unresolved
no resolver link, observed 2026-08-01T17:38:09.384123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T17:38:09.384123Z digest=sha256:882281f8046718d9f1fc5f2b3ef5240fbc3b415f714e93ebf36318bdbc557dc3