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Paper Citation Record · LEDGER

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2301.10921.

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

pith.paper-citation-record.v1
2301.10921 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:40:23.139316Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:39:51.061224Z

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 aa11776c-7e6c-47c0-8ae8-eaa674edd804 · inbound

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence cites this paper.

Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-12T04:58:47.873008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:58:47.873008Z digest=sha256:c7928c71d802e479ada48a8b5397bc4c7a355b7d1f02f541145db37ed2a0525d

Observation 3356102d-bf09-4bbc-bbdf-b56ad19ca949 · inbound

Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision cites this paper.

Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-16T12:40:23.139316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:40:23.139316Z digest=sha256:e09d35b781dc72b39dbee23e38930d90674201ad91f8aa419fa89c38149a0253

Observation 2b6611cd-413c-4b15-9b8c-87cc0a5cb3d5 · inbound

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization cites this paper.

FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.293146Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.293146Z digest=sha256:e798aca782ae76a7eb6923fa141706df23cc100f8048f615ccfd621758dfbd51

Observation 97d63b39-3e23-4a97-b389-d6aa7391939c · inbound

DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample cites this paper.

DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T16:48:59.843029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:48:59.843029Z digest=sha256:8a59adc6164a8740dfcef9e7985e3029095ac9e2f8d203a0d5a1496c24cc8c10

Observation 6ce14a2d-dea3-4ad7-82be-09aa60af95cc · inbound

Normality Calibration in Semi-supervised Graph Anomaly Detection cites this paper.

Normality Calibration in Semi-supervised Graph Anomaly Detection SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T12:48:07.716713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T12:48:07.716713Z digest=sha256:7133e87b31427b0455b764d09d99be92a4a63b9a8ce083561ed8e75af9b1dbef

Observation 0b5eabb8-1af6-4dc0-aa17-82ba837a448f · inbound

Can LLMs Learn to Reason Robustly under Noisy Supervision? cites this paper.

Can LLMs Learn to Reason Robustly under Noisy Supervision? SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:08:01.291816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-05-13T16:58:42.129870Z digest=sha256:41c7d2a6c1a416a288ab8e8302a1f7d6b38cf9ff6a0f64f06d4f9bc7c8bc0f71

Observation 4e47cc19-8acc-4ec8-bad2-b968513871a0 · inbound

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling cites this paper.

GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 65

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T06:06:40.802839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=arxiv_source observed=2026-06-28T07:45:43.320339Z digest=sha256:091bc144f2eed9604cf65e980a3a56d0cd04139668e45ca29bd1d6e9b92f81e2

Observation 8727a159-6904-4202-868d-8ee4a893de64 · inbound

Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning cites this paper.

Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T13:39:51.062733Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-26T05:00:28.839647Z digest=sha256:3e00984697acc934ecbc0b493cc71ac770097afaa7c21e62a8e9d77788710713

Observation e52fa7ff-92fb-42bc-af25-0672e6032847 · inbound

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms cites this paper.

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-06-30T06:14:19.384462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-06-30T06:09:54.742202Z digest=sha256:96cbd0141b5df6bc716b3c2b1b5d157bc5dff827e9fa497c0e40e670773633fa

Observation 62628055-b4da-464d-9dac-cca90b2199cd · inbound

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms cites this paper.

APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 226

Resolution
verified exact
arxiv_id, observed 2026-07-01T06:45:29.611997Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-01T06:38:06.306930Z digest=sha256:b4439865555482be1b8e446a84762f160b84a4c7caa2ba8413283538fb713921

Observation a108f77c-8401-4255-bfe9-631d3467e0eb · inbound

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition cites this paper.

PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:47:08.995273Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-07-02T16:45:46.207051Z digest=sha256:752fa7e864a915dbd9c5ea0752453e1b6df2a7a137f244ad1c055cf11a292dfb

Observation b3290dcc-d6b6-459a-bdcf-3e07b4e89f33 · inbound

Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation cites this paper.

Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T04:20:35.525838Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T04:20:35.525838Z digest=sha256:1f3b928d28f4ffabaf76156e0cfde8ca7b78add689ab14640c0d3e773f03a212