{"as_of":"2026-08-22T23:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:42e0fab6ae8ab75e1e12ba34ccaf85e5a612c1c80020253a408416984593fcd1","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:40:23.139316Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-04T13:39:51.061224Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-12T04:58:47.873008Z","title":"In NeurIPS","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"2412.00883","last_updated":"2024-12-01T16:44:27Z","snapshot_observed_at":"2026-08-14T15:29:07.281838Z","submitted_at":"2024-12-01T16:44:27Z","title":"Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-12T04:58:47.873008Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2412.00883"},"observation_digest":"sha256:c7928c71d802e479ada48a8b5397bc4c7a355b7d1f02f541145db37ed2a0525d","observation_id":"aa11776c-7e6c-47c0-8ae8-eaa674edd804","resolution":{"observed_at":"2026-08-12T04:58:47.873008Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-16T12:40:23.139316Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.12132","last_updated":"2025-04-16T14:45:26Z","snapshot_observed_at":"2026-08-20T19:13:56.009647Z","submitted_at":"2025-04-16T14:45:26Z","title":"Weakly Semi-supervised Whole Slide Image Classification by Two-level Cross Consistency Supervision","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-16T12:40:23.139316Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2504.12132"},"observation_digest":"sha256:e09d35b781dc72b39dbee23e38930d90674201ad91f8aa419fa89c38149a0253","observation_id":"3356102d-bf09-4bbc-bbdf-b56ad19ca949","resolution":{"observed_at":"2026-08-16T12:40:23.139316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-06T22:44:04.293146Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20841","last_updated":"2025-06-25T21:25:05Z","snapshot_observed_at":"2026-08-20T19:13:09.915895Z","submitted_at":"2025-06-25T21:25:05Z","title":"FixCLR: Negative-Class Contrastive Learning for Semi-Supervised Domain Generalization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T22:44:04.293146Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2506.20841"},"observation_digest":"sha256:e798aca782ae76a7eb6923fa141706df23cc100f8048f615ccfd621758dfbd51","observation_id":"2b6611cd-413c-4b15-9b8c-87cc0a5cb3d5","resolution":{"observed_at":"2026-08-06T22:44:04.293146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-15T16:48:59.843029Z","title":"arXiv preprint arXiv:2301.10921 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.20516","last_updated":"2025-08-28T07:57:54Z","snapshot_observed_at":"2026-08-20T19:15:04.780535Z","submitted_at":"2025-08-28T07:57:54Z","title":"DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-15T16:48:59.843029Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2508.20516"},"observation_digest":"sha256:8a59adc6164a8740dfcef9e7985e3029095ac9e2f8d203a0d5a1496c24cc8c10","observation_id":"97d63b39-3e23-4a97-b389-d6aa7391939c","resolution":{"observed_at":"2026-08-15T16:48:59.843029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-04T12:48:07.716713Z","title":"Gccad: Graph contrastive coding for anomaly detection.IEEE Trans- actions on Knowledge and Data Engineering, 35(8):8037–8051, 2022a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2510.02014","last_updated":"2026-06-06T02:07:58Z","snapshot_observed_at":"2026-08-20T05:45:15.047991Z","submitted_at":"2025-10-02T13:36:04Z","title":"Normality Calibration in Semi-supervised Graph Anomaly Detection","version":3},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-04T12:48:07.716713Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2510.02014"},"observation_digest":"sha256:7133e87b31427b0455b764d09d99be92a4a63b9a8ce083561ed8e75af9b1dbef","observation_id":"6ce14a2d-dea3-4ad7-82be-09aa60af95cc","resolution":{"observed_at":"2026-08-04T12:48:07.716713Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2604.03993","last_updated":"2026-04-05T06:30:50Z","snapshot_observed_at":"2026-07-06T22:53:01.835843Z","submitted_at":"2026-04-05T06:30:50Z","title":"Can LLMs Learn to Reason Robustly under Noisy Supervision?","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T16:58:42.129870Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2604.03993"},"observation_digest":"sha256:41c7d2a6c1a416a288ab8e8302a1f7d6b38cf9ff6a0f64f06d4f9bc7c8bc0f71","observation_id":"0b5eabb8-1af6-4dc0-aa17-82ba837a448f","resolution":{"observed_at":"2026-05-13T17:08:01.291816Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2606.04516","last_updated":"2026-06-03T06:47:50Z","snapshot_observed_at":"2026-07-06T23:44:37.797802Z","submitted_at":"2026-06-03T06:47:50Z","title":"GeoMin: Data-Efficient Semi-Supervised RLVR via Geometric Distribution Modeling","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-06-28T07:45:43.320339Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2606.04516"},"observation_digest":"sha256:091bc144f2eed9604cf65e980a3a56d0cd04139668e45ca29bd1d6e9b92f81e2","observation_id":"4e47cc19-8acc-4ec8-bad2-b968513871a0","resolution":{"observed_at":"2026-07-02T06:06:40.802839Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2606.26973","last_updated":"2026-06-25T12:45:42Z","snapshot_observed_at":"2026-08-07T06:47:33.957579Z","submitted_at":"2026-06-25T12:45:42Z","title":"Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-06-26T05:00:28.839647Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2606.26973"},"observation_digest":"sha256:3e00984697acc934ecbc0b493cc71ac770097afaa7c21e62a8e9d77788710713","observation_id":"8727a159-6904-4202-868d-8ee4a893de64","resolution":{"observed_at":"2026-07-04T13:39:51.062733Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2606.30577","last_updated":"2026-06-30T14:59:05Z","snapshot_observed_at":"2026-08-09T05:01:54.786056Z","submitted_at":"2026-06-29T17:20:26Z","title":"APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-30T06:09:54.742202Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2606.30577"},"observation_digest":"sha256:96cbd0141b5df6bc716b3c2b1b5d157bc5dff827e9fa497c0e40e670773633fa","observation_id":"e52fa7ff-92fb-42bc-af25-0672e6032847","resolution":{"observed_at":"2026-06-30T06:14:19.384462Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2606.30577","last_updated":"2026-06-30T14:59:05Z","snapshot_observed_at":"2026-08-09T05:01:54.786056Z","submitted_at":"2026-06-29T17:20:26Z","title":"APRIL-MedSeg: A Modular Medical Image Segmentation Toolbox Embracing Modern Paradigms","version":2},"reference_index":226,"source":"pdf_text","source_observed_at":"2026-07-01T06:38:06.306930Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2606.30577"},"observation_digest":"sha256:b4439865555482be1b8e446a84762f160b84a4c7caa2ba8413283538fb713921","observation_id":"62628055-b4da-464d-9dac-cca90b2199cd","resolution":{"observed_at":"2026-07-01T06:45:29.611997Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":"2301.10921","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-07-04T13:39:51.061224Z","title":"Softmatch: Addressing the quantity-quality trade-off in semi-supervised learning","venue":null,"work_id":"75a10026-f3b2-4718-a4ee-32e20134b883","year":2023},"citing_paper":{"arxiv_id":"2607.00358","last_updated":"2026-07-01T02:57:06Z","snapshot_observed_at":"2026-08-03T00:30:16.187890Z","submitted_at":"2026-07-01T02:57:06Z","title":"PRISM: Prioritized Channel Importance with Semi-supervised Domain Adaptation for Cross-Subject EEG Emotion Recognition","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-02T16:45:46.207051Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2607.00358"},"observation_digest":"sha256:752fa7e864a915dbd9c5ea0752453e1b6df2a7a137f244ad1c055cf11a292dfb","observation_id":"a108f77c-8401-4255-bfe9-631d3467e0eb","resolution":{"observed_at":"2026-07-02T16:47:08.995273Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.10921","snapshot_observed_at":"2026-08-14T04:20:35.525838Z","title":"Softmatch: Addressing the quantity-quality trade- off in semi-supervised learning.arXiv preprint arXiv:2301.10921, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.09052","last_updated":"2026-08-10T03:00:17Z","snapshot_observed_at":"2026-08-22T19:49:42.532406Z","submitted_at":"2026-08-10T03:00:17Z","title":"Triple Expert Learning from Noisy Labels for Semi-Supervised Vision Foundation Model Adaptation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T04:20:35.525838Z"},"links":{"cited_paper":"/paper/2301.10921","citing_paper":"/paper/2608.09052"},"observation_digest":"sha256:28f6b4a0bfdf7a37f31b5e537c8ae3006bedd105af1737cf0c095d752749ad54","observation_id":"b3290dcc-d6b6-459a-bdcf-3e07b4e89f33","resolution":{"observed_at":"2026-08-14T04:20:35.525838Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2301.10921/citation-record","integrity":"/paper/2301.10921/integrity","json":"/paper/2301.10921/citation-record.json","paper":"/paper/2301.10921"},"outbound":[],"paper":{"arxiv_id":"2301.10921","last_updated":"2023-03-15T15:49:07Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-21T23:16:40.487035Z","submitted_at":"2023-01-26T03:53:25Z","title":"SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"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."}