{"as_of":"2026-08-04T09:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2c34c594deacfe35a17cfd120fe8d8c0af5ea673684866683ed6cf7e220d0aa4","coverage":[{"denominator":40,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":40,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T00:25:18.564814Z","state":"measured"},{"denominator":40,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":40,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+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/2604.20928/citation-record","integrity":"/paper/2604.20928/integrity","json":"/paper/2604.20928/citation-record.json","paper":"/paper/2604.20928"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A novel deep denoising model integrating transformer and time–frequency loss for gearbox fault diagnosis","venue":null,"work_id":"e7923419-cb82-4886-812f-ab92775ca0eb","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:8d87ca7156a2479c78481f8480a2ae9deecc13ffa4bc3c747d527124b00989cd","observation_id":"c181d8d4-a7a3-424f-b8e5-124097b601d9","resolution":{"observed_at":"2026-05-23T11:22:53.734776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"VibrMamba: A lightweight Mamba-based fault diagnosis of rotating machinery using vibration signal","venue":null,"work_id":"72655689-7ae7-4eea-bb13-0ceb3d805c77","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:8a828453fa3f9fec11237dd2de3ef9cd3746017da390d46486cd8305fbb32d37","observation_id":"eeb50e86-d2ee-4420-8d75-1ab628cc8332","resolution":{"observed_at":"2026-05-23T11:22:53.759735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Large language models for fault diagnosis","venue":null,"work_id":"589b3338-9b27-476d-b7d2-9743c942115d","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:2cd4da1d13ac59a7ce85d995bc6b220b4aa101e71e41a20bac1fc5587529399b","observation_id":"661b260a-9fb1-4524-919a-a4af4e2e3e6d","resolution":{"observed_at":"2026-05-23T11:22:53.845873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-07-06T23:23:03.018068Z","title":"Deep learning","venue":null,"work_id":"5e93d2f9-b0e0-4f66-a450-c580920b44b6","year":2015},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:2adbeebb54d2c3c89ed374a4ac286e538830ea3227d19a549b59fae12e644069","observation_id":"d41ee0fc-37ca-457f-8bec-b402742f7cd1","resolution":{"observed_at":"2026-05-23T11:22:53.739699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Review of intelligent fault diagnosis for rotating machinery under imperfect data conditions","venue":null,"work_id":"c92afb23-7be4-4a8d-87ab-9bb98981269e","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:dd0632240ee8b6881254288f20d245e89e7d7fb28f7f58aeefd6738cee1ab529","observation_id":"39c7f387-ca94-42b0-953e-4eb2282de6a9","resolution":{"observed_at":"2026-05-23T11:22:53.726708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain generalization for cross-domain fault diagnosis: An application-oriented perspective and a benchmark study","venue":null,"work_id":"2385acaf-6ecd-47c7-98ef-53f78722dad6","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:6df5ac865e59144d1f27890a069caa7957f8e382efaabf40aaa58fda7b12ccaa","observation_id":"dce70a8e-a57a-4648-9948-92e135c97f24","resolution":{"observed_at":"2026-05-23T11:22:53.743604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Fault diagnosis in rotating machines based on transfer learning: Literature review","venue":null,"work_id":"fa52a5e2-abd3-4039-a614-bd30724b7c83","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:a9acc7f08a7e2f499ae5fcf1484359836cf4b6cdc2ec677430dc57b5861a2e04","observation_id":"555599ac-47d8-4941-a6ea-af45508f42ae","resolution":{"observed_at":"2026-05-23T11:22:53.803126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Progressive transfer learning: An intelligent fault diagnosis method for unlabeled rotating machinery with small samples","venue":null,"work_id":"a5660ff4-c1ec-4b76-bc07-dd4cc585f2cd","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:e57d01285d524a3498d36959497047c6a651e0f8bb2b2af184320d9b5d4ce531","observation_id":"d6058c76-0d70-4a93-9b56-be0bd2718047","resolution":{"observed_at":"2026-05-23T11:22:53.779204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Universal domain adaptation in rotating machinery fault diagnosis: A self-supervised orthogonal clustering approach","venue":null,"work_id":"1e47a053-f66b-47d0-b4c5-356501ec96f9","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:cab0c80d92f79edcf64fa29c9bad4151f3109a9e08036fb29f0d770b5a4178cc","observation_id":"ed55cf0f-224e-43f3-b94a-19ddae509d89","resolution":{"observed_at":"2026-05-23T11:22:53.751630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2510.16033","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Global-focal adaptation with information separation for noise-robust transfer fault diagnosis","venue":null,"work_id":"b2acc71b-bec6-4e7b-a186-a13fbbc2e4c1","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:168f6cc0cc672ece9ad33ffd40d653437e7aa34f0b6fafc03d11ced43a1724fc","observation_id":"9ef564d3-bdb3-46d5-8258-129cfe523cce","resolution":{"observed_at":"2026-05-10T00:29:47.522880Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Enhancing bear- ing fault diagnosis in real damages: A hybrid multi-domain generalization network for feature comparison","venue":null,"work_id":"5f5f4cb4-a9e9-4601-9bed-5df3982368b0","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:855588491d638a4d43d3d6d37fd2bfe666d78722d49ef6c591853d504373b018","observation_id":"f00b545f-b183-421d-ba05-3c5ec6bed0b2","resolution":{"observed_at":"2026-05-23T11:22:53.755600Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain generalization for rotating machinery fault diagnosis: A survey","venue":null,"work_id":"579f3829-849b-4683-8813-adb74f08b212","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:06bdaba52e3723ccf4448068b711ac2de693b9e6291d2a97b784d60a2bbadf23","observation_id":"83762afb-8057-4b5c-800a-ac9759123760","resolution":{"observed_at":"2026-05-23T11:22:53.853675Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A two-stage semi- supervised domain generalization network for fault diagnosis under unknown working conditions","venue":null,"work_id":"b33a408c-4aa3-4448-9a42-ea43c3f13a5c","year":2026},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:dcd62f00894dd5c30c136e6808cb2660806c9ee0abc056f4c709b7536a47d734","observation_id":"3b505afd-634f-4deb-900f-d8f461d98c3d","resolution":{"observed_at":"2026-05-23T11:22:53.747669Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Semi-supervised dynamic generalization network with dual feature enhancement strat- egy for machinery fault diagnosis under unseen working conditions","venue":null,"work_id":"b01956e9-69f9-4d87-908a-29c0dcc196e9","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:dbecfa5f7bed176660f340307916ab042aad2ebcff13366869ade5b4feac9b2e","observation_id":"421f6d7e-06c0-4c06-9fbe-827487b31834","resolution":{"observed_at":"2026-05-23T11:22:53.807617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Deep semisupervised domain generalization network for rotary machinery fault diagnosis under variable speed","venue":null,"work_id":"ae3be4e9-351e-4084-b766-57daf277492c","year":2020},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:cd98024b1dfbd1bfb87321c4ab8b13fb2f255d555fe3d38c35df0bb201d26051","observation_id":"37bd23fa-6dc6-4f56-86ed-9b915b5bc696","resolution":{"observed_at":"2026-05-23T11:22:53.730946Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain fuzzy generalization networks for semi-supervised intelligent fault diagnosis under unseen working conditions","venue":null,"work_id":"0ce312e3-de58-483b-bbe5-826077795bcf","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:afabca9a08955be45207d3c1ac4a5d9be441260e7d70e3952eff698137f24d23","observation_id":"0d6b531e-fd9a-4692-a538-6077cf73e38c","resolution":{"observed_at":"2026-05-23T11:22:53.722607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Mutual-assistance semisupervised domain generalization network for intelligent fault diagnosis under unseen working conditions","venue":null,"work_id":"5e07cb8a-1a6e-4c43-af32-59bfad0c9e54","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:2341e41e7c09f5c44126e30c2290532826cff98c89a2861544e57962c53c2a65","observation_id":"9eacd77d-797d-4dab-86df-da42e0815b99","resolution":{"observed_at":"2026-05-23T11:22:53.819140Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Contrast-assisted domain- specificity-removal network for semi-supervised generalization fault diagnosis","venue":null,"work_id":"cbaa553d-6c9b-48d7-98dd-478e26b8a40d","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:e4acdfb7c6459becf7e05e0935eafdc5e7dafce690c1686b9dd15450d306793a","observation_id":"24e55bfc-4f80-417a-9a1d-411812d29a94","resolution":{"observed_at":"2026-05-23T11:22:53.766489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Semi-supervised domain general- ization with clustering and contrastive learning combined mechanism","venue":null,"work_id":"06ba2494-29ec-41e1-8c92-dd9685de5d02","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:233a0ce9af2d006627f1fb570f4c316d825a4bf99dc43a3ca066d91774c369c9","observation_id":"20910f94-0961-4fd4-a1e7-4b8c5270c722","resolution":{"observed_at":"2026-05-23T11:22:53.717939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain knowledge guided pseudo-label generation framework for semi-supervised domain generalization fault diagnosis","venue":null,"work_id":"7c175612-347c-407a-b1da-8b8a3912264c","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:a1504b5e55a6c6e13de55daec155104c2cf6634d254055d93c8c135447f0e703","observation_id":"af89015e-61a6-4bdb-af35-7c7a9eee7062","resolution":{"observed_at":"2026-05-23T11:22:53.858245Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A noise-resilient fault diagnosis method based on optimized residual networks","venue":null,"work_id":"2bc14322-5e19-4eaf-b610-1acf49a38c97","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:3fc70b44440d4dbf818c43a954fd07cb5e13612a4573c5bec670b0ecdbd098cd","observation_id":"4b7f8422-ce07-4e5d-be63-a8a35a3cadcb","resolution":{"observed_at":"2026-05-23T11:22:53.842209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"UDDGN: Domain- independent compact boundary learning method for universal diagnosis domain generation","venue":null,"work_id":"71a77276-387c-4a39-ac41-b1ca707a8b06","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:5ea000a280ec39d886e33597059863e38f9946fee23fe03c094a67a0df12bac5","observation_id":"5ac2b3d1-57ec-47bd-a9f6-de4ed811fc62","resolution":{"observed_at":"2026-05-23T11:22:53.822817Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain augmentation generalization network for real-time fault diagnosis under unseen working conditions","venue":null,"work_id":"c37df6de-4ebb-478d-9add-c279267dace6","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:8dc2bb3c393b7a07bc945a57235f3cfb66a0653fea6153989e3e3597b47db008","observation_id":"5d7c1409-1a79-485f-89f2-d16f7559ce50","resolution":{"observed_at":"2026-05-23T11:22:53.775215Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain generalization network based on inter-domain multivariate linearization for intelligent fault diagnosis","venue":null,"work_id":"e41980b8-44e9-4cd3-891a-71d1b4d51f88","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:543e89d5179307e5efeba343367eafdb7cb918bed65eef8f39c42c4453f8300b","observation_id":"3c1bb861-6bfb-4c1d-9421-2daca3c08a1b","resolution":{"observed_at":"2026-05-23T11:22:53.811176Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Multiple classifiers inconsistency-based deep adversarial domain generalization method for cross-condition fault diagnosis in rotating systems","venue":null,"work_id":"818ab4a2-c5be-47f8-ac83-cd4e7e2d1c1b","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:2b4c26cb21d996f46b457f7e4d258f71880458cb53e0be702cd821fdfcddf752","observation_id":"29e935ab-ffa6-4e1b-b89a-1091111ae789","resolution":{"observed_at":"2026-05-23T11:22:53.827105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A domain feature decoupling network for rotating machinery fault diagnosis under unseen operating conditions","venue":null,"work_id":"afbb996a-13cc-4994-8dd0-1df4ac60941d","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:b440b04d6c0f8ac25c4cb4a953a65b731feebca667a8e3711d092f4f4af811f0","observation_id":"4205f6c0-32ff-4271-9f0a-708d02fb774f","resolution":{"observed_at":"2026-05-23T11:22:53.783076Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Causality-inspired multi- source domain generalization method for intelligent fault diagnosis under unknown operating conditions","venue":null,"work_id":"820ff973-28be-4632-a45f-7eb312834025","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:6e40dd7c2739e1ed9aa0998dff2ef4ee1cef4ada81e970b816c8fd9ba054c04f","observation_id":"f53d498d-014a-4a5a-8d4d-c599dee013b5","resolution":{"observed_at":"2026-05-23T11:22:53.763359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Meta-learning based domain generaliza- tion framework for fault diagnosis with gradient aligning and semantic matching","venue":null,"work_id":"ac1c75f2-73ca-44f0-981d-f9bb49263aff","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:4ceea5dc62420286ca5f7b6382abf25e142ccc8199c5e361b15937628abeda54","observation_id":"f138dca6-16f3-4d1e-976a-845ff43c538b","resolution":{"observed_at":"2026-05-23T11:22:53.795054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain-augmented meta ensemble learning for mechanical fault diagnosis from heteroge- neous source domains to unseen target domains","venue":null,"work_id":"e6155893-96b4-4026-aaa4-cec6fbc12bf6","year":2025},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:e1f5da5d98b14de0807d0cc6c7da4a7b0f1a443a32d17e99ecb01f9000bdcab2","observation_id":"9aafc4e9-f678-4dda-94bc-d390dfc93d8a","resolution":{"observed_at":"2026-05-23T11:22:53.838753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A new adversarial domain generalization network based on class boundary feature detection for bearing fault diagnosis","venue":null,"work_id":"642b061a-2a35-4186-8179-a4c2518d6e33","year":2022},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:5a05f599d29b631b3a1a5ab40c90ed2d0a0a6242a8e887c2e1c47dd08c9a23e8","observation_id":"ce1e9ca9-2bb2-450d-81da-a924f08e69b0","resolution":{"observed_at":"2026-05-23T11:22:53.791507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain-invariant feature fusion networks for semi-supervised generalization fault diag- nosis","venue":null,"work_id":"8df4bdc6-463a-4eff-8f6c-7c454f18bdfe","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:5dbb10e023b2b7d58bd8ba5cf2ce11821dd908bf501e93e2ff83fddde53450ad","observation_id":"eed35f8e-3597-4f38-8a9c-8163c96da804","resolution":{"observed_at":"2026-05-23T11:22:53.831028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Domain-adversarial training of neural networks","venue":null,"work_id":"9c826952-4165-48b8-979c-db2ca08f18d7","year":2016},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:05b4bc0abe40336e5b756fe87fbe1853d23739ae3e19aa6478951dc52c23c624","observation_id":"4d326522-c59b-4b5a-a3e1-45f3caaf23c8","resolution":{"observed_at":"2026-05-23T11:22:53.799329Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1807.03748","last_updated":"2019-01-22T18:47:12Z","snapshot_observed_at":"2026-07-06T06:49:24.960992Z","submitted_at":"2018-07-10T16:52:11Z","title":"Representation Learning with Contrastive Predictive Coding","version":2},"cited_work":{"arxiv_id":"1807.03748","doi":"10.1609/aaai.v36i10.21390","metadata_source":"pith","pith_arxiv_id":"1807.03748","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Representation Learning with Contrastive Predictive Coding","venue":"cs.LG","work_id":"7b08a1d4-d565-424e-9c86-6ef244b7b90a","year":2018},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"cited_paper":"/paper/1807.03748","citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:a630dad866ab1b8b1b406c04028d27dafddcd82a54759bcb79198da4c72ec45d","observation_id":"6a13c875-c077-4dd9-9a2b-d690b52fc2bc","resolution":{"observed_at":"2026-05-10T00:29:47.525338Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Fuzzy sets","venue":null,"work_id":"31fc365e-46e3-41b9-92f8-9e4a9baf7ebd","year":1965},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:d284e69d25498b9521c7a9ece72b4e1eb5d26d20ddbc9aaaf37e7bdc3265b902","observation_id":"57942b63-1b2e-4408-a85a-ac802591b8a5","resolution":{"observed_at":"2026-05-23T11:22:53.712158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Rolling element bearing diagnostics using the case western reserve university data: A benchmark study","venue":null,"work_id":"18eb60ab-63fe-470c-9f70-c47c1f7d1a3e","year":2015},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:4816181173dacf36850b2116c948910ad55fdf5abd0a84ec5fc87a3ec6fcc39f","observation_id":"975b1a9c-1537-4b7b-bc05-2c811b125599","resolution":{"observed_at":"2026-05-23T11:22:53.815014Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Condition monitoring of bearing damage in electromechanical drive systems by using motor current signals of electric motors: A benchmark data set for data-driven classification","venue":null,"work_id":"409406ab-328d-4bf2-bc3d-48e401f900e8","year":2016},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:6b845de35496ca2d3b8e34bec17478cc82191600f866aa091dc6e086699d7323","observation_id":"c6f9267b-b840-4788-a682-02f40500eecf","resolution":{"observed_at":"2026-05-23T11:22:53.787905Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Study of JUST slewing bearing failure test data","venue":null,"work_id":"974d0a6a-a190-4ca8-904e-964f65846128","year":2024},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:b644050cc4cc12e2ade67dc07f20c595ffac97d588d8c890a181eafe09413f06","observation_id":"a8ee4f0b-7d07-4027-851c-b1955f74aa8f","resolution":{"observed_at":"2026-05-23T11:22:53.849836Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Rotating machinery fault-induced vibration signal modulation effects: A review with mecha- nisms, extraction methods and applications for diagnosis","venue":null,"work_id":"9aaf48f7-970d-4ad8-bcb4-0d645f079cc9","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:296bc81f2958552f707a810e3efb2cbdb25409cb8abc60de0c1f37d35d845254","observation_id":"011d97e5-4494-4ac3-93af-0cc3e7b8a2bd","resolution":{"observed_at":"2026-05-23T11:22:53.862193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"ConvNeXt V2: Co-designing and scaling convnets with masked autoencoders","venue":null,"work_id":"87cb6cb6-07dc-4265-afdc-2d899865477c","year":2023},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:6263bfbf683306edd790fb662086837da619e1f082eca5fcc889a73f97260d7e","observation_id":"54f99753-a0d7-41f2-94dd-de4f6722fb32","resolution":{"observed_at":"2026-05-23T11:22:53.834581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Evaluation: From precision, recall and F-measure to ROC, informedness, markedness & correlation","venue":null,"work_id":"cad375df-a983-4076-9b6c-ae52d601730d","year":2011},"citing_paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-10T00:25:18.564814Z"},"links":{"citing_paper":"/paper/2604.20928"},"observation_digest":"sha256:bda39268304798489b92e468d931719d3b6b53831e7d69f00cba2a6e7b457473","observation_id":"1b1ecb16-99a8-4f7c-b602-ff378942d147","resolution":{"observed_at":"2026-05-23T11:22:53.770749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.20928","last_updated":"2026-04-22T08:41:27Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T23:07:36.996629Z","submitted_at":"2026-04-22T08:41:27Z","title":"Domain-Aware Hierarchical Contrastive Learning for Semi-Supervised Generalization Fault Diagnosis"},"reference_resolution":{"displayed":40,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":2,"verified_fuzzy":38},"total_outbound_references":40},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2604.20928."}