{"as_of":"2026-08-08T01:10:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:af0b0334a7a119cd76c588097898698a6f31862dfca8544ee1ad0597c88e5b75","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:30:34.946094Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.02366/citation-record","integrity":"/paper/2506.02366/integrity","json":"/paper/2506.02366/citation-record.json","paper":"/paper/2506.02366"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.526101Z","title":"Adversarial robustness of streaming algorithms through impor- tance sampling,","venue":null,"work_id":"78c3ebbf-8577-45dd-8e03-0a03e6a7a1b1","year":2021},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.767083Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:a9ddcc9ac3ebefeea0bc4820a2147257f090c9c0c8456ca6bd35e4254394559a","observation_id":"ea7eda7b-a542-4a07-a217-fff68a0e5d50","resolution":{"observed_at":"2026-08-07T11:30:35.529742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.514354Z","title":"Distilling effective supervision from severe label noise,","venue":null,"work_id":"72e8d253-2633-4ffd-8efc-5a28fa8cc00e","year":2020},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.771590Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:35d6efdd02ecb8fb9628ecd9944e8edc410c6460f87195b5768a2f960e19e2fd","observation_id":"e1eb5be9-762b-4709-a26c-dbe4987758e5","resolution":{"observed_at":"2026-08-07T11:30:35.518235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2008.04636","last_updated":"2020-08-11T11:41:53Z","snapshot_observed_at":"2026-08-02T15:54:31.740553Z","submitted_at":"2020-08-11T11:41:53Z","title":"A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2008.04636","snapshot_observed_at":"2026-08-07T11:30:34.776194Z","title":"A comparison of synthetic oversampling meth- ods for multi-class text classification. arxiv 2020,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.776194Z"},"links":{"cited_paper":"/paper/2008.04636","citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:df68c3caa53e8ef3c3a25ff04a252beee2489875d3e9030a32259434abb527a0","observation_id":"8a77755b-72d4-42b0-a094-1d2da15a2d6e","resolution":{"observed_at":"2026-08-07T11:30:34.776194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.501572Z","title":"Coreset sampling from open-set for fine-grained self-supervised learning,","venue":null,"work_id":"4d2e7763-4ffd-4b81-9002-72cb8ced204f","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.781249Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:909a1785cbef55978cca6b4202f5c6a9b3c32f370f473364e06717438d16a079","observation_id":"d07cf0c9-9d45-4910-8d83-81b47e639072","resolution":{"observed_at":"2026-08-07T11:30:35.506241Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.487976Z","title":"Pointasnl: Robust point clouds processing using nonlocal neural networks with adaptive sampling,","venue":null,"work_id":"59a35e03-ee70-46de-be36-ad048e753988","year":2020},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.786045Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:20c9a16a120a205a597205bc99c079e5fec94d4d9b3c2273728e4756edb4d0ca","observation_id":"df730c2a-b0c3-48da-9194-7c0137a2a37e","resolution":{"observed_at":"2026-08-07T11:30:35.492818Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.474990Z","title":"Attention-based point cloud edge sampling,","venue":null,"work_id":"452b6a34-dafa-4fe5-af58-ca571b698dba","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.790263Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:fb927b10b1ad998cbd12d6f3a71624103cf297479ce647959019b00a28362c2b","observation_id":"2e35610a-48e5-47ab-8ac8-bc3084235afc","resolution":{"observed_at":"2026-08-07T11:30:35.478845Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.13821","last_updated":"2022-08-04T10:25:40Z","snapshot_observed_at":"2026-08-07T17:24:03.888611Z","submitted_at":"2021-09-28T15:48:22Z","title":"Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.13821","snapshot_observed_at":"2026-08-07T11:30:34.794851Z","title":"Diffusion-based voice conversion with fast maximum likelihood sam- pling scheme,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.794851Z"},"links":{"cited_paper":"/paper/2109.13821","citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:148149c0e5bb4747aa783900c75a5e3cd9993f842a1da009b6a242950f3ad1d2","observation_id":"bf6a37d3-8d93-4b24-8718-48335111518a","resolution":{"observed_at":"2026-08-07T11:30:34.794851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.462420Z","title":"Unsupervised sampling promoting for stochastic human trajectory prediction,","venue":null,"work_id":"430e4c61-a04d-4212-a316-13ab1a75910c","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.798640Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:0ae1952b338752d9f5294ba922ea669cb7b5c43864f29c26d9a83069493052de","observation_id":"fbcc252b-f6e2-4055-b99e-da9c7aebdc47","resolution":{"observed_at":"2026-08-07T11:30:35.466419Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.450216Z","title":"Model-based synthetic sampling for imbal- anced data,","venue":null,"work_id":"85c40119-111b-4653-8b83-552b2583983e","year":2020},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.802680Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:fc09e8d1575f1bc11cb8ed79c9a3b677c980f0226caba7d065dc835689822c8e","observation_id":"4378cc85-ca16-4879-b7d8-e781e251d436","resolution":{"observed_at":"2026-08-07T11:30:35.453957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.437199Z","title":"A robust oversampling approach for class imbalance problem with small disjuncts,","venue":null,"work_id":"568fa2b0-cb08-4385-afa3-dc647c0936c2","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.806518Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:ec0393435aca70730167ab91edb0450e9145170d536322a7f14303e9701311f0","observation_id":"f60bc015-1350-4f4e-ad19-049f80541702","resolution":{"observed_at":"2026-08-07T11:30:35.441873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.424535Z","title":"A review of methods for imbalanced multi-label classification,","venue":null,"work_id":"0bfed5cc-2e55-47cc-9ed3-4ad4bdd4e01d","year":2021},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.809971Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:26618e5c9ca0178e53682e22c32b2ebf55ff5dc99366c1270e1ed652db59ce91","observation_id":"3ada6b1c-230a-443f-a84a-64d5f31c334d","resolution":{"observed_at":"2026-08-07T11:30:35.428467Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.814292Z","title":"Borderline-smote: a new over- sampling method in imbalanced data sets learning,","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.814292Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:88212c0557c910f27709ce9a77f4fdd66057e6162bb7c1fd16d52f6594ab51a7","observation_id":"ee9953fc-761d-43ac-a451-62bc8e8c76eb","resolution":{"observed_at":"2026-08-07T11:30:34.814292Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.818131Z","title":"Deepsmote: Fusing deep learning and smote for imbalanced data,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.818131Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:eb55586a4769f690892ab42e53a6ec2a6f2832f013d64820acc6313a3c660aac","observation_id":"14d9f1c0-e71c-41f8-8062-8fe23feff423","resolution":{"observed_at":"2026-08-07T11:30:34.818131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.395255Z","title":"Adasyn- random forest based intrusion detection model,","venue":null,"work_id":"1bd3df12-9d83-4286-8d8c-7235dd670383","year":2021},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.821578Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:e467d04dd11a0c354fe9a83840d8b03c83d338dab8fc12e040fb5542f336d9a2","observation_id":"6a94290d-57d5-4467-95b1-7302579dc07b","resolution":{"observed_at":"2026-08-07T11:30:35.399459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.382768Z","title":"Abnormal samples oversampling for anomaly detection based on uniform scale strategy and closed area,","venue":null,"work_id":"9f4dfdf6-5243-4e85-bb0f-b38749ff3793","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.825316Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:5c8a513ac6aa8e84df35c3f890602a1dae8deeb8c315645e6d8902d5c1cade4e","observation_id":"ec1c1d77-cf84-4246-a558-117b3521f48a","resolution":{"observed_at":"2026-08-07T11:30:35.386856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.370486Z","title":"Two modifications of cnn,","venue":null,"work_id":"2d8e2492-3a89-4dbe-90b7-d7e5dc7c013a","year":1976},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.829097Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:0534c429c14805ac4eb94b77a1ea844706d68a3ca066e5b617079df09bbd0893","observation_id":"70aa08ec-84c1-4fb0-b595-82a704443d37","resolution":{"observed_at":"2026-08-07T11:30:35.373911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.832968Z","title":"Random sampling with a reservoir,","venue":null,"work_id":null,"year":1985},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.832968Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:06106116c68c423841e96f6b621fada5218858062689e448068d359da18e3dc9","observation_id":"712cc73b-8794-4b07-b6c5-a061cc75e9b5","resolution":{"observed_at":"2026-08-07T11:30:34.832968Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.350445Z","title":null,"venue":null,"work_id":"07f5d68e-fe12-4a60-afcc-2aa472ec8be2","year":2013},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.836632Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:b3ec0a6f442c9406d82a77d7295acf4b59abc564cb3b01a7f4afc663116a3040","observation_id":"3bc97d92-dbb4-487b-a99a-5fcd60ceb27e","resolution":{"observed_at":"2026-08-07T11:30:35.353889Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.338075Z","title":null,"venue":null,"work_id":"54a7e0b1-38e1-471e-8d47-f8dac93e64f2","year":2019},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.840470Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:ef460b8ae14f4adbe1e6fb383c94b4cc272f1ea719554950a7019cc3ecf8ce38","observation_id":"928186d4-b436-4c97-b7dc-8335f4899d32","resolution":{"observed_at":"2026-08-07T11:30:35.342031Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.844084Z","title":"Random forests,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.844084Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:bb2bef13b9548a6ebdac9fc55872501572a2c845570fb01f5ae3d770a3006b3e","observation_id":"985b283f-690c-4099-91b1-bce68a55b184","resolution":{"observed_at":"2026-08-07T11:30:34.844084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.316407Z","title":"Fuzzy sets and information granularity,","venue":null,"work_id":"dbce60e5-2a7c-40ef-a703-c4dbd07985ad","year":1979},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.848647Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:33fb1556d52336661b4e0e1d950639d1aa6ebd999b1ab5f0e0e8ca1206170d37","observation_id":"b705bb23-381a-407f-8956-134855788fc0","resolution":{"observed_at":"2026-08-07T11:30:35.321092Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.852375Z","title":"Granular ball computing classifiers for efficient, scalable and robust learning,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.852375Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:75f935a46ab9dd19d1a8946e3d4574ab13fbdd0e561710755c028f38c7dab956","observation_id":"ee39f389-ef40-4f07-bb40-f819f60a97d8","resolution":{"observed_at":"2026-08-07T11:30:34.852375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.295062Z","title":"Granular ball sampling for noisy label classification or imbalanced classification,","venue":null,"work_id":"8926cfdb-017f-43b4-bb28-2dfc9ad0cf95","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.856261Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:8783d83dd82fe2b8cdbb7705d592e638a966d73c1b820e2449ffcdf67f8b0ad7","observation_id":"ea0b1d45-3623-4eb3-b86a-fa434d6c0cff","resolution":{"observed_at":"2026-08-07T11:30:35.298752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.283052Z","title":"k-times markov sampling for svmc,","venue":null,"work_id":"c0cb9312-9a94-465f-80b1-10d715c17bf0","year":2018},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.860093Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:313aa9ebd9eab568254a660d2d434095e91c2320252ab8ae7fcb050b85c14c19","observation_id":"9ba2588f-6f4a-40d0-b362-3e3ddba15ab0","resolution":{"observed_at":"2026-08-07T11:30:35.286832Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.270567Z","title":"Reduction of training data for support vector machine: a survey,","venue":null,"work_id":"6282c718-c80f-43a8-8551-343a57354d48","year":2022},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.863758Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:c7e413de23d107b1a4d4424c79092165f119e4a06ca4e97e89edc1a315948bde","observation_id":"66deeb00-58e6-4420-bd8d-afbea38760f6","resolution":{"observed_at":"2026-08-07T11:30:35.274399Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.258775Z","title":"A method to improve support vector machine based on distance to hyperplane,","venue":null,"work_id":"b2d4c9be-860f-4c6c-8372-7d8e73047801","year":2015},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.867296Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:9abf2e5c62a7f6d70295fd5f61d09ebb949899da951c4eee80a04adb4c4b0793","observation_id":"99462150-c753-4533-b70b-d56f2cfd5dd7","resolution":{"observed_at":"2026-08-07T11:30:35.262528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.246087Z","title":"An efficient and adaptive granular-ball generation method in classification problem,","venue":null,"work_id":"f0a14142-5ea1-4357-addd-3d786c4d9a08","year":2024},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.870930Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:6f1f3f6334295e24f73fc5dbb6d84460085a5f456fc5c95e53f3e00204a3196e","observation_id":"f5bf6bcc-421f-442e-991d-81a3cf6f5657","resolution":{"observed_at":"2026-08-07T11:30:35.250256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.875029Z","title":"3wc- gbnrs++: A novel three-way classifier with granular-ball neighborhood rough sets based on uncertainty,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.875029Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:99b8c77f0b705876bbe82f6009458a71cf4669c16134ba4824375bfaa530e771","observation_id":"758cffb9-1064-4ff0-ad8b-c62f03a5c3a3","resolution":{"observed_at":"2026-08-07T11:30:34.875029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.223835Z","title":"A fast granular-ball-based density peaks clustering algorithm for large-scale data,","venue":null,"work_id":"9d79bfa1-0958-4303-9309-b50b032626c8","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.878821Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:627bcd7dd9881c2e515ffb2bb48f5bd1bbe9af0d25ba4d55338bd751841deee6","observation_id":"67932a58-e72f-48c0-8077-8ed8c75d5698","resolution":{"observed_at":"2026-08-07T11:30:35.228672Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.883000Z","title":"An efficient spectral clustering algorithm based on granular-ball,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.883000Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:27b9fde1c4f0cd53b1811664db80cc02498ccc93b549c23f71ba3ac0622c04bb","observation_id":"d3e5727e-e315-4470-8594-a84a89da1485","resolution":{"observed_at":"2026-08-07T11:30:34.883000Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.202370Z","title":"W-gbc: An adaptive weighted clustering method based on granular-ball structure,","venue":null,"work_id":"adf7e1d2-0764-4bf6-9c8f-8935aa407872","year":2024},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.886414Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:2adfe3fd6232d624387629aa7d468088f850f23bb5d09b845ed710c8e52b2899","observation_id":"ab477aa0-bc3c-4add-9ae8-dca3a619d132","resolution":{"observed_at":"2026-08-07T11:30:35.206327Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.890100Z","title":"Granular-ball fuzzy set and its implement in svm,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.890100Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:3a2984463ae556a683b735473a76d079c4c0b465be753edf2a12d9592f67dfff","observation_id":"7982ab4b-4272-457f-9d51-2c8abb58e3fb","resolution":{"observed_at":"2026-08-07T11:30:34.890100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.179972Z","title":"Incremental learning based on granular ball rough sets for classifica- tion in dynamic mixed-type decision system,","venue":null,"work_id":"ac3172ca-10fd-47a1-acef-5483ca75e785","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.893754Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:343051796fc39985cb2628aa1f72f944a6a87b7370d46feffb96376dbaf15b67","observation_id":"59ea1f43-1c14-4830-8fae-467c1caf4afc","resolution":{"observed_at":"2026-08-07T11:30:35.184538Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.167624Z","title":"Open continual feature selection via granular-ball knowledge transfer,","venue":null,"work_id":"f8d67e2e-3287-45ea-94ce-1972d50d05d6","year":2024},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.897322Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:3a07691ca6addd3cd791b4c1177b83578ef3abedd39389f5b465c17e347a5ae4","observation_id":"27a365d7-89d0-426f-9bd4-12a90159e307","resolution":{"observed_at":"2026-08-07T11:30:35.171544Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.154325Z","title":"Gbnrs: A novel rough set algorithm for fast adaptive attribute reduction in classification,","venue":null,"work_id":"489eb28e-2c79-4239-b8b1-c280915e6e5e","year":2022},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.900913Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:7be15b1c520215b9c73f73b3e56b0ecc8ef5dd56c648d97837f37579c84270e4","observation_id":"a349d63a-240e-4418-8c2a-29c6a6a6aacc","resolution":{"observed_at":"2026-08-07T11:30:35.158270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.140867Z","title":"Grrs: Accurate and efficient neighborhood rough set for feature selection,","venue":null,"work_id":"6f3cf127-3796-4e15-99f1-dd2a020086d7","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.904296Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:c2182e0c38ea6e761c108af303c1fc328b79baecd97cd651878cbf210e198069","observation_id":"8d7a0a11-c271-4592-a046-964562369f7f","resolution":{"observed_at":"2026-08-07T11:30:35.145181Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.02388","last_updated":"2023-03-04T11:39:46Z","snapshot_observed_at":"2026-08-05T15:47:53.017940Z","submitted_at":"2023-03-04T11:39:46Z","title":"Graph-based Representation for Image based on Granular-ball","version":1},"cited_work":{"arxiv_id":"2303.02388","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.02388","snapshot_observed_at":"2026-08-07T11:30:34.981764Z","title":"Graph-based Representation for Image based on Granular-ball","venue":"cs.CV","work_id":"78056fb1-71bd-4ad7-9fed-b6e333090efa","year":2023},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.908154Z"},"links":{"cited_paper":"/paper/2303.02388","citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:c00906d7c453adbd9355660f983ca6cc9882e3deb4c5bb6e8f450fc1f30e7de9","observation_id":"9198eef9-276d-46a5-83f6-a29ecf30ce8c","resolution":{"observed_at":"2026-08-07T11:30:34.988301Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.912437Z","title":"Gbg++: A fast and stable granular ball generation method for clas- sification,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.912437Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:4ab32d10978c6b68b87c8a7b8bc7908c24d9029af8af83f0fbcf845331b74aba","observation_id":"89ad8326-17f6-4773-8a7b-1bd6bf2079a8","resolution":{"observed_at":"2026-08-07T11:30:34.912437Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.916239Z","title":"Smote: synthetic minority over-sampling technique,","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.916239Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:08b688726390075e5534a2cd6aa19cc04ffe833446edd7796f3b663e976fde99","observation_id":"0639534b-e43f-4272-bf20-d307e9f62e67","resolution":{"observed_at":"2026-08-07T11:30:34.916239Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.920045Z","title":"Nearest neighbor pattern classification,","venue":null,"work_id":null,"year":1967},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.920045Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:d33a47afc77390f453dd5ed2f4ba8fca5d92aa506472d876a4caf69bf12e63cf","observation_id":"597bf2cf-b3dd-4356-92eb-86258abf06b1","resolution":{"observed_at":"2026-08-07T11:30:34.920045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.099866Z","title":"Clas- sification and regression trees,","venue":null,"work_id":"7b108b35-8ac4-47d8-bf77-e286b3e31a8e","year":1984},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.923931Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:42e3533811275788f0877c4f4bd4539113bff4b0a74f811c940dbfd687f74f9f","observation_id":"d4b4cc68-ae85-44a5-95ad-8e900006cda9","resolution":{"observed_at":"2026-08-07T11:30:35.103690Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.927572Z","title":"Lightgbm: A highly efficient gradient boosting decision tree,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.927572Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:c05c4685585ee880e41075b13512bc2ef57cc8d53c69441daef6d4aeb53ee66f","observation_id":"e1cbfc4c-16fa-462b-904a-95022bc3f5db","resolution":{"observed_at":"2026-08-07T11:30:34.927572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:34.931118Z","title":"Xgboost: A scalable tree boosting system,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.931118Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:125ed9ce6bfdc7927933e1d6ab5810f9b7e63d17266c1a90b7ead3104bb63f23","observation_id":"e63dd8eb-2b48-4c40-800a-938ce10f5cbf","resolution":{"observed_at":"2026-08-07T11:30:34.931118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.068811Z","title":null,"venue":null,"work_id":"db62ab17-1687-4027-976e-b0313cf4428b","year":2022},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.934491Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:9595f22ef781d7c722e1f63997c9b842d7a5d580c323be415181ff66dae46a53","observation_id":"9bddce1a-9c50-4378-bcfe-c9e7e63b9fa9","resolution":{"observed_at":"2026-08-07T11:30:35.073092Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.055111Z","title":"Keel data-mining software tool: Data set repository, integration of algorithms and experi- mental analysis framework,","venue":null,"work_id":"d0fae5b4-ae91-44bd-8ef0-96e859bc67ff","year":2015},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.938693Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:72c7791d8de9e056d13d06b6b5db7fd6f8955dea05c59b2882fcb531533aa335","observation_id":"01bc80e4-ae5f-43c3-8e76-06462b407669","resolution":{"observed_at":"2026-08-07T11:30:35.059337Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.041578Z","title":"The use of machine learning methods in classification of pumpkin seeds (cucurbita pepo l.),","venue":null,"work_id":"f0942b74-ca57-4cbf-b8f3-bf0a6724a519","year":2021},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.942155Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:5d83fcede2bf9d8c806a93d5cdccafd7f64ffcf6932ca361cecfc4529a78f0d7","observation_id":"5bb6a5f5-287b-4169-a4b1-95ec73783706","resolution":{"observed_at":"2026-08-07T11:30:35.045779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:30:35.027758Z","title":"Speed up kernel discriminant analysis,","venue":null,"work_id":"888ed637-d348-44e0-9e7f-83bc00b55e47","year":2011},"citing_paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:30:34.946094Z"},"links":{"citing_paper":"/paper/2506.02366"},"observation_digest":"sha256:7201f197656c68e85780248ecfb4f336ef47c70c1482e702e93baa1cbadf71a3","observation_id":"0c972fdd-29d8-45a4-86f7-89490ef2ebc4","resolution":{"observed_at":"2026-08-07T11:30:35.031977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.02366","last_updated":"2025-06-03T02:04:27Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T11:23:05.382246Z","submitted_at":"2025-06-03T02:04:27Z","title":"Approximate Borderline Sampling using Granular-Ball for Classification Tasks"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":28},"total_outbound_references":47},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.02366."}