{"as_of":"2026-08-10T10:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:70e8a3713b5010b07472d636ce30a8a5ceaefc570dee78f29e8246c1035b466b","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T14:36:34.741919Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2507.18464/citation-record","integrity":"/paper/2507.18464/integrity","json":"/paper/2507.18464/citation-record.json","paper":"/paper/2507.18464"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:36:35.594516Z","title":"In: Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining","venue":null,"work_id":"48e06f0f-5c44-46e2-b3ee-94224d4e4c46","year":2015},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.556071Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:da9a0e0bf18ca952d47f2029bdf0087a61d488db0185d7ba5ef64bf2e621a4e8","observation_id":"df9746b6-5d62-4162-a941-e7b3ad809ce5","resolution":{"observed_at":"2026-08-06T14:36:35.610237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.575342Z","title":"In: Proceedings of the 2007 SIAM international conference on data mining","venue":null,"work_id":"26a13f5b-63f6-4ec7-864b-ca4f9cc9deb0","year":2007},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.561427Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:76b2e177f628fa5c387f90dc5fe02e0d61dc52399df2671a1b9776af22e78aef","observation_id":"50388fdd-5edc-4329-9f30-abebcf4468fc","resolution":{"observed_at":"2026-08-06T14:36:35.580798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.555370Z","title":"In: Joint European conference on machine learning and knowledge discovery in databases","venue":null,"work_id":"b87daf14-ebcd-4d6d-881c-1fd1c6ca1217","year":2010},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.566459Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:68fa533047ebd1e6868a65ef100b41ff3529637c38ee4b793c85ad8962f03da6","observation_id":"1454a823-305e-4a70-8023-40f601c08c38","resolution":{"observed_at":"2026-08-06T14:36:35.562195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.533948Z","title":"Journal of Machine Learning Research - Proceedings Track11, 44–50 (2010)","venue":null,"work_id":"96bd55dd-34a2-499b-bfa1-21becd415faa","year":2010},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.584902Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:fcf494cca888ab0cf953b9022fbd1813c0a54692fa937e8e9e98cefb93edb7b4","observation_id":"e826187e-e074-4a80-a0bc-55364d089b2a","resolution":{"observed_at":"2026-08-06T14:36:35.540730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:34.598182Z","title":"Routledge (1984)","venue":null,"work_id":null,"year":1984},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.598182Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:a377c496a1c81246ec71e4dec2bf720939e2b7d9d639e4299e2ff1e30fcc7447","observation_id":"5ba28425-b420-463b-80de-26a2c0e0d29a","resolution":{"observed_at":"2026-08-06T14:36:34.598182Z","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":"10.1016/j.ins.2013.12.011","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"Information Sciences265, 50–67 (May 2014)","venue":"Information Sciences","work_id":"82113333-837b-4537-8be2-30f6566e8acc","year":2014},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.604567Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:46ae51ffb09a215c38b0935fcee5f3a97bb2d880466273b8b84f4b79d6ce447d","observation_id":"355170c0-cb55-489a-b436-5f153da3b295","resolution":{"observed_at":"2026-08-06T14:36:34.912505Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/978-3-031-82346-6_1","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T00:03:56.115653Z","title":"In: Piangerelli, M., Prenkaj, B., Rotalinti, Y., Joshi, A., Stilo, G","venue":"Lecture notes in computer science","work_id":"09898265-d336-4f72-8551-fcc5515c29cf","year":2025},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.610814Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:6570b98e0f9e76bfa3fb985bfc12f0944149a37d12ee65ba6063bcd49db8592f","observation_id":"05e816b0-1266-4c36-b5de-42c79646f17f","resolution":{"observed_at":"2026-08-06T14:36:34.889985Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1206.6422","last_updated":"2012-06-27T19:59:59Z","snapshot_observed_at":"2026-07-06T02:50:47.096675Z","submitted_at":"2012-06-27T19:59:59Z","title":"An Online Boosting Algorithm with Theoretical Justifications","version":1},"cited_work":{"arxiv_id":"1206.6422","doi":"10.48550/arxiv.1206.6422","metadata_source":"pith","pith_arxiv_id":"1206.6422","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"An Online Boosting Algorithm with Theoretical Justifications","venue":"cs.LG","work_id":"e990798a-d452-4ad2-b047-7ea29407dc25","year":2012},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.617011Z"},"links":{"cited_paper":"/paper/1206.6422","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:18f6dbaf0a1a8688ae4b47798a43ef8bf8cf4c32aa818f20d61e3c0c6be464d0","observation_id":"741395c3-66e4-4f78-87ac-5a203c3be3fe","resolution":{"observed_at":"2026-08-06T14:36:34.867405Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2401.06066","last_updated":"2024-01-11T17:31:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-01-11T17:31:42Z","title":"DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.06066","snapshot_observed_at":"2026-08-06T14:36:34.622349Z","title":"https://doi.org/10.48550/ARXIV.2401.06066,https://arxiv","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.622349Z"},"links":{"cited_paper":"/paper/2401.06066","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:84f0a23744eead98e178f3494cace46a5f2c7863e5ca19b1a0c77d0d991ca6c7","observation_id":"f2ae1637-b718-472f-802a-bc8690b79545","resolution":{"observed_at":"2026-08-06T14:36:34.622349Z","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":"2026-08-06T14:36:35.515915Z","title":"In: Proceedings ofthesixthACMSIGKDDinternationalconferenceonKnowledgediscovery and data mining","venue":null,"work_id":"1bb0e542-88cc-4e54-86d4-ef110deac6e0","year":2000},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.628349Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:f4182feed1261dfdce90f7efc3c84a706626135af00e8b8f5f0e6e4f829502ec","observation_id":"1d0a5573-2607-454f-b072-4c4763552132","resolution":{"observed_at":"2026-08-06T14:36:35.521121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.03961","last_updated":"2022-06-16T20:36:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-01-11T16:11:52Z","title":"Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsity","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.03961","snapshot_observed_at":"2026-08-06T14:36:34.638105Z","title":"https://doi.org/10.48550/ARXIV.2101.03961,https: //arxiv.org/abs/2101.03961 DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts 15","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.638105Z"},"links":{"cited_paper":"/paper/2101.03961","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:086f43f50539c81a5c47868c3f3a8a0c0424265c4ae655bef07d8aea16916155","observation_id":"e38cce36-410b-481a-b335-4b31a18805c9","resolution":{"observed_at":"2026-08-06T14:36:34.638105Z","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":"2026-08-06T14:36:35.498819Z","title":"ACM computing surveys (CSUR)46(4), 1–37 (2014)","venue":null,"work_id":"8d9192c9-7947-4809-bc45-1628188f8915","year":2014},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.643188Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:b66233b15e366c85ab0c66eff51227c6e61f557798cc08cc9d9443f062127d3f","observation_id":"5d367107-89e5-414e-be8a-f50fbd8ba548","resolution":{"observed_at":"2026-08-06T14:36:35.504385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.477068Z","title":"In: Proceedings of the 2nd International Workshop on MetaOS for the Cloud-Edge-IoT Continuum","venue":null,"work_id":"941936b8-777a-43b4-a3e1-558a8084868b","year":2025},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.653348Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:932833b343045b3934703ce5ae785938e268097cd24d20e88e62047fe1a1661a","observation_id":"4605fec0-1726-44b4-9bed-d1feb7919075","resolution":{"observed_at":"2026-08-06T14:36:35.484629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.454736Z","title":"Machine Learning pp","venue":null,"work_id":"4ce4b23b-a686-4f93-995b-bd37da6dce32","year":2017},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.658384Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:acc6bdb0011ab05cf99261c81276afb5213487c970983927f147af96a9d5d2c2","observation_id":"9d43ff74-9a31-4cbb-aa77-5ada6e61af88","resolution":{"observed_at":"2026-08-06T14:36:35.461730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.07432","last_updated":"2026-04-13T10:51:33Z","snapshot_observed_at":"2026-08-05T12:19:28.129345Z","submitted_at":"2025-02-11T10:20:04Z","title":"CapyMOA: Efficient Machine Learning for Data Streams and Online Continual Learning in Python","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.07432","snapshot_observed_at":"2026-08-06T14:36:34.663437Z","title":"https://doi.org/10.48550/ARXIV.2502.07432","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.663437Z"},"links":{"cited_paper":"/paper/2502.07432","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:a7c419bb0b349b0321371d18aec230a5894e96c1987accfbcbd556a53f3a7023","observation_id":"7e724d0b-4108-43dc-b63d-be2a9a761652","resolution":{"observed_at":"2026-08-06T14:36:34.663437Z","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":"2026-08-06T14:36:35.430173Z","title":"In: 2019 IEEE International Conference on Data Mining (ICDM)","venue":null,"work_id":"7b1c0688-4319-4ddc-9041-d5bcdd2e1c90","year":2019},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.668681Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:e27b1adaee80d69b3a369df8997f7276957de760b674b76cee4baad519bdd847","observation_id":"c6dca97e-fd1e-45f0-8310-a00119af61b0","resolution":{"observed_at":"2026-08-06T14:36:35.436161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:34.673240Z","title":"Neural computation3(1), 79–87 (1991)","venue":null,"work_id":null,"year":1991},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.673240Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:2b68e2c0a4d288cec90df89e0c2035edcebe890e78232ba04275bef550e19c51","observation_id":"9bd0cef6-bf77-422a-b76c-fab380d06e86","resolution":{"observed_at":"2026-08-06T14:36:34.673240Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.16437","last_updated":"2025-02-19T14:35:07Z","snapshot_observed_at":"2026-07-06T18:35:54.300599Z","submitted_at":"2024-06-24T08:29:58Z","title":"Theory on Mixture-of-Experts in Continual Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.16437","snapshot_observed_at":"2026-08-06T14:36:34.678116Z","title":"arXiv preprint arXiv:2406.16437 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.678116Z"},"links":{"cited_paper":"/paper/2406.16437","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:9c048b1dd8564df6da096abec86d01c541d53926d89ff4a03d807140a50d32fa","observation_id":"9c823260-410f-4a47-bffd-6a1ef00f8768","resolution":{"observed_at":"2026-08-06T14:36:34.678116Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.09762","last_updated":"2024-08-30T13:39:56Z","snapshot_observed_at":"2026-08-03T20:52:43.208598Z","submitted_at":"2023-10-15T07:20:28Z","title":"Diversifying the Mixture-of-Experts Representation for Language Models with Orthogonal Optimizer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.09762","snapshot_observed_at":"2026-08-06T14:36:34.682826Z","title":"arXiv preprint arXiv:2310.09762 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.682826Z"},"links":{"cited_paper":"/paper/2310.09762","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:41d749eee75dc8ca502615e4def86e431ff835a5cc07aabab03a6775abc3aa02","observation_id":"621dc4d0-93ac-4c44-ae06-5368ef565309","resolution":{"observed_at":"2026-08-06T14:36:34.682826Z","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":"2026-08-06T14:36:35.390739Z","title":"Frontiers in psychology4, 504 (2013)","venue":null,"work_id":"e33238d1-7dd6-4a81-8338-bd54dfd48595","year":2013},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.689163Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:53cd11594d4883c079626e784b77002073d46e185bb6971c4b3e00af4165e099","observation_id":"c647a0c1-a642-4119-be9c-d80661e827c8","resolution":{"observed_at":"2026-08-06T14:36:35.397365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.373267Z","title":"In: International Workshop on Artificial Intelligence and Statistics","venue":null,"work_id":"481a9293-f72b-4702-8c0f-d3ccb66dcd45","year":2001},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.696916Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:b5ebabcd30375516243320ffb271ebf5b6dc9a2f451cac295dc37afd9a4ff8fc","observation_id":"fa9507b7-f493-4e68-a489-1b6842062fab","resolution":{"observed_at":"2026-08-06T14:36:35.378267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1701.06538","last_updated":"2017-01-23T18:10:00Z","snapshot_observed_at":"2026-07-06T05:27:13.416519Z","submitted_at":"2017-01-23T18:10:00Z","title":"Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1701.06538","snapshot_observed_at":"2026-08-06T14:36:34.702152Z","title":"arXiv preprint arXiv:1701.06538 (2017)","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.702152Z"},"links":{"cited_paper":"/paper/1701.06538","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:bda0a0c7c2076bfe005e392036f1f3b0ed8b5fbc1929c1b83cc3ec34f4842d9e","observation_id":"8583c28d-68bb-464e-af3e-93ee09998035","resolution":{"observed_at":"2026-08-06T14:36:34.702152Z","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":"2026-08-06T14:36:35.348168Z","title":"In: Proceedings of the seventh ACM SIGKDD interna- tional conference on Knowledge discovery and data mining","venue":null,"work_id":"87e61f4a-3494-4c84-a0a2-121f233c49bc","year":2001},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.709052Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:072d835f917bbbe7bd14f46ffb9332e7d2915befab2c2b3d9692da1694f9de5b","observation_id":"8f837ade-c075-4d73-9c22-6de2ba7fa406","resolution":{"observed_at":"2026-08-06T14:36:35.359889Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.310587Z","title":"Expert Systems with Applications213, 118934 (2023)","venue":null,"work_id":"be9945ee-f1e4-4e87-8c42-81abccd334ae","year":2023},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.716861Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:3dfb7be5c793ef528674196863be7ffd2f43dda5e1a81272e6e81fe1eb71ad54","observation_id":"c7c04d65-063a-4871-affc-6b0ec71c15fa","resolution":{"observed_at":"2026-08-06T14:36:35.315490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:35.288387Z","title":"Technical Report: TCD-CS-2004-15, Department of Computer Science Trin- ity College, Dublin (2004) 16 Aspis, Cajas Ordoñez, et al","venue":null,"work_id":"30cb1c3e-ad63-48a1-b4d4-138dee605bd7","year":2004},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.723673Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:12d98412f1623abff7102b8b59542402f08e27ec0e879018fd86f8e3875deb8e","observation_id":"6b791407-3ec7-400d-aa06-cdbd143a1498","resolution":{"observed_at":"2026-08-06T14:36:35.296050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01739","last_updated":"2024-03-27T10:21:24Z","snapshot_observed_at":"2026-08-02T08:17:59.108390Z","submitted_at":"2024-01-29T12:05:02Z","title":"OpenMoE: An Early Effort on Open Mixture-of-Experts Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01739","snapshot_observed_at":"2026-08-06T14:36:34.730135Z","title":"arXiv preprint arXiv:2402.01739 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.730135Z"},"links":{"cited_paper":"/paper/2402.01739","citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:e79e2e03c470a23d821a6006cf8b8b7f5f4382d2d4472a4b22402eb6aeea3662","observation_id":"2b0bf067-c69d-4ec8-b383-927122089b02","resolution":{"observed_at":"2026-08-06T14:36:34.730135Z","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":"2411.2024","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T14:36:35.106932Z","title":"In: 2024 IEEE 24th International Conference on Communication Technology (ICCT)","venue":null,"work_id":"0b1fb290-a44e-4208-b786-efb9e7b6cd87","year":2024},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.735941Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:9abc0adab48f82c4b1d2e8169bb2ded29b75e0dce8548a69ffeb437cdb0df40f","observation_id":"a4cea0da-54a2-420c-9d44-170bb7a9cc08","resolution":{"observed_at":"2026-08-06T14:36:35.139935Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-06T14:36:34.741919Z","title":"Machine Learning98(3), 455–482 (Apr 2014)","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T14:36:34.741919Z"},"links":{"citing_paper":"/paper/2507.18464"},"observation_digest":"sha256:c68507a088836c38bbdaee783109babe678a892d059105f1c840ca748356324b","observation_id":"3a417a22-cafb-4b70-9732-65f2a3ff1a17","resolution":{"observed_at":"2026-08-06T14:36:34.741919Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.18464","last_updated":"2025-07-24T14:39:20Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-08T23:43:23.195177Z","submitted_at":"2025-07-24T14:39:20Z","title":"DriftMoE: A Mixture of Experts Approach to Handle Concept Drifts"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":10,"verified_exact":3,"verified_fuzzy":14},"total_outbound_references":28},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2507.18464."}