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Paper Citation Record · LEDGER

Self-Training: A Survey

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2202.12040.

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

pith.paper-citation-record.v1
2202.12040 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:32:11.308966Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T06:28:05.484131Z

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 3a915dfd-3f9d-48e2-86a2-b86e9c1a0674 · inbound

Large Language Models Can Self-Improve cites this paper.

Large Language Models Can Self-Improve Self-Training: A Survey

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-18T17:00:48.293382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T17:00:48.167441Z digest=sha256:161b6d66b56c2a182fd3ae035fed4319955d6e4e130f2807693ae6bdf37fcd0f

Observation 20d4a219-d394-4691-a8f3-2baf046cbe3a · inbound

Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing cites this paper.

Self-Boost via Optimal Retraining: An Analysis via Approximate Message Passing Self-Training: A Survey

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:11.308966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:11.308966Z digest=sha256:5e81286eedcfdd13268ffe91f4dedfffa6fcb74239804a22b6257e2cf400a7c8

Observation 5b9ff56e-2def-4394-a580-ede4826a1aac · inbound

ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection cites this paper.

ADAPT: A Pseudo-labeling Approach to Combat Concept Drift in Malware Detection Self-Training: A Survey

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T18:19:59.732045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:19:59.732045Z digest=sha256:1902341c401ae8498a8d716c8dfe102515e49e80de125f57ff9ea7d46ff7d1c9

Observation 9c267596-dd47-4a67-bc64-5bbcc2a1eb38 · inbound

Improving Data and Parameter Efficiency of Neural Language Models Using Representation Analysis cites this paper.

Improving Data and Parameter Efficiency of Neural Language Models Using Representation Analysis Self-Training: A Survey

Reference 146

Resolution
unresolved
no resolver link, observed 2026-08-06T17:03:46.369486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:03:46.369486Z digest=sha256:15fa4874b73741a7da716ac4882f2ab902277193fb797b6d2bce63436301dbbc

Observation 31b8f2e2-ae22-4731-98c3-46f2654f88fb · inbound

Embarrassingly Simple Self-Distillation Improves Code Generation cites this paper.

Embarrassingly Simple Self-Distillation Improves Code Generation Self-Training: A Survey

Reference 3

Resolution
unresolved
no resolver link, observed 2026-07-13T14:33:35.834383Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T14:33:35.834383Z digest=sha256:e3289e9b589d38e97e2d143233d47f49fe829a954b64a61e161c3c5949458e34

Observation 51da0c39-9689-44b6-a0f1-1261a2713b14 · inbound

SAGE: Scalable Automatic Gating Ensemble for Confident Negative Harvesting in Fraud Detection cites this paper.

SAGE: Scalable Automatic Gating Ensemble for Confident Negative Harvesting in Fraud Detection Self-Training: A Survey

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-20T06:28:05.485710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-20T06:26:02.477422Z digest=sha256:8b4491735a89e31c76e3e2a13a134e82a46f951a0deaa224697b86865c55f40d