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Paper Citation Record · LEDGER

A Survey on Programmatic Weak Supervision

As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:2202.05433.

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

pith.paper-citation-record.v1
2202.05433 v2

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 2026-08-21T06:32:19.484+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T20:42:37.150999Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T02:25:19.666416Z

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 d0bcd06a-b47b-4825-a987-7bd1d0b9a64f · inbound

Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks cites this paper.

Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks A Survey on Programmatic Weak Supervision

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T20:42:37.150999Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:42:37.150999Z digest=sha256:19f92f62678c32e7902edf6c1de1c41e8edd7324b0f7e0bc90e25def12f420b1

Observation 6e42ec6d-4d2d-4fad-8645-e9c5e6b2c813 · inbound

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble cites this paper.

Harnessing Multiple Large Language Models: A Survey on LLM Ensemble A Survey on Programmatic Weak Supervision

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-23T02:25:19.668521Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-23T02:22:28.649071Z digest=sha256:c7127d8625e9ecaae55c8c4b5d1889f7cf4b14a2089f7581df3021008ac1cf7a

Observation 786d2e69-08f7-4803-a8d8-e065e40912eb · inbound

Refining Labeling Functions with Limited Labeled Data cites this paper.

Refining Labeling Functions with Limited Labeled Data A Survey on Programmatic Weak Supervision

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T12:50:35.903602Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:50:35.903602Z digest=sha256:dec74e69c7ed494aa45345b3d178ad025f661d0fd1dd32bac4d13d1ee6ae9b6f

Observation 2e8b8e2d-43f4-4bcc-b6c1-510c5ac2ddbd · inbound

Weak Supervision for Real World Graphs cites this paper.

Weak Supervision for Real World Graphs A Survey on Programmatic Weak Supervision

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:26:47.432114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:26:47.432114Z digest=sha256:35ff472aa08a5db35edbee73eebb637b0e215c990fad33244cde89f484b5b721

Observation 41b904eb-310f-4635-a96f-be0397848f14 · inbound

Meta-learning Representations for Learning from Multiple Annotators cites this paper.

Meta-learning Representations for Learning from Multiple Annotators A Survey on Programmatic Weak Supervision

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-07T04:40:25.737399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:40:25.737399Z digest=sha256:cecfb8249a3df1f67c71c763cbd5730997e0bc8a3807f82087f908913045a67c

Observation 922ea992-5839-4689-b6f9-61ebfb670af1 · inbound

Importance of User Control in Data-Centric Steering for Healthcare Experts cites this paper.

Importance of User Control in Data-Centric Steering for Healthcare Experts A Survey on Programmatic Weak Supervision

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T15:03:45.843358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:03:45.843358Z digest=sha256:3fa906dd81161c74b0432e00ef083d6a47089f43c85a4865b6d7df18a9f4136d

Observation 71be5a8e-c3db-4331-bd93-a70355b58c0a · inbound

SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data cites this paper.

SynthEHR-Eviction: Enhancing Eviction SDoH Detection with LLM-Augmented Synthetic EHR Data A Survey on Programmatic Weak Supervision

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T18:47:53.603967Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:47:53.603967Z digest=sha256:779b10c79684ae0ad26c5aba18dfaaeafa4b8e9449917f95eff287ea23dd099b

Observation 8895219a-0088-4aa9-bb5b-69cb83900c4d · 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 A Survey on Programmatic Weak Supervision

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T17:03:34.278926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:03:34.278926Z digest=sha256:b3344a522ee6a62f00c1f99f26a9a30b019822f8eb41ed06617c4978aadd55f8

Observation a3a8498e-1130-4a28-a3b1-ed6e565b749b · inbound

Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise cites this paper.

Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise A Survey on Programmatic Weak Supervision

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T08:56:01.636712Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-10T16:24:38.758066Z digest=sha256:8d482ed53ae0cfe07981484c03c9543692c5e8220f00b48457132017acbcacbd