{"as_of":"2026-08-18T11:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:9604b063678145a832b3fbfc026548afa5619daddd6e007af898b2f145b95c72","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T22:39:23.269495Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-01T09:15:44.195185Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-08-12T15:59:30.064161Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.13740","last_updated":"2024-11-20T22:49:28Z","snapshot_observed_at":"2026-08-16T20:01:10.375909Z","submitted_at":"2024-11-20T22:49:28Z","title":"Federated Continual Learning for Edge-AI: A Comprehensive Survey","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T15:59:30.064161Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2411.13740"},"observation_digest":"sha256:f9f594ba2ee2bc963731f484ab404e9e4e8c065f0a069e5f3a400ecc816797ad","observation_id":"45d05268-b9b2-4043-8c82-a540e9d81809","resolution":{"observed_at":"2026-08-12T15:59:30.064161Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-08-08T13:56:54.354719Z","title":"Usmanova, F","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.07059","last_updated":"2025-07-04T00:22:16Z","snapshot_observed_at":"2026-08-12T16:58:42.494413Z","submitted_at":"2025-02-10T21:51:02Z","title":"Federated Continual Learning: Concepts, Challenges, and Solutions","version":2},"reference_index":257,"source":"pdf_text","source_observed_at":"2026-08-08T13:56:54.354719Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2502.07059"},"observation_digest":"sha256:39a00d5bddca4448699e3b92fcce1536f0db1ffacfdadc567e6f3a14f7c2858a","observation_id":"620df9f4-b103-43c0-a9d5-d40f2301998d","resolution":{"observed_at":"2026-08-08T13:56:54.354719Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-08-15T22:39:23.269495Z","title":"A distillation- based approach integrating continual learning and federated learning for pervasive services,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.01965","last_updated":"2025-05-10T17:42:01Z","snapshot_observed_at":"2026-08-16T02:58:06.858414Z","submitted_at":"2025-05-10T17:42:01Z","title":"TaskVAE: Task-Specific Variational Autoencoders for Exemplar Generation in Continual Learning for Human Activity Recognition","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T22:39:23.269495Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2506.01965"},"observation_digest":"sha256:cf57775a29a7244294245452d0f7d89376e733e81154342681cfec79efe761e3","observation_id":"a7bddb1a-25e4-4145-b20e-d688fcf0a1d2","resolution":{"observed_at":"2026-08-15T22:39:23.269495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-08-03T07:36:56.321711Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services.CoRR, abs/2109.04197, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2601.19788","last_updated":"2026-07-16T11:04:23Z","snapshot_observed_at":"2026-08-16T08:04:47.697278Z","submitted_at":"2026-01-27T16:50:48Z","title":"Knowledge-Aware Evolution for Task-Free Streaming Federated Continual Learning with Arbitrary Class Overlap","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T07:36:56.321711Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2601.19788"},"observation_digest":"sha256:0e5d0a4c1d42c5154e926d16be46a2ab5d72ec18042ea4ba69c014a2f4bfb475","observation_id":"a9ffe2ce-97af-4c8d-9964-6bf1682e8232","resolution":{"observed_at":"2026-08-03T07:36:56.321711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-08-15T15:46:21.691185Z","title":"A distillation-based ap- proach integrating continual learning and federated learning for pervasive services.arXiv preprint arXiv:2109.04197,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2601.22274","last_updated":"2026-05-28T17:13:40Z","snapshot_observed_at":"2026-08-17T15:08:48.161373Z","submitted_at":"2026-01-29T19:44:15Z","title":"Server-Proximal Aggregation for Federated Domain-Incremental Learning under Partial Participation: Task-Uniform Convergence and Backward Transfer","version":2},"reference_index":2011,"source":"pdf_text","source_observed_at":"2026-08-15T15:46:21.691185Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2601.22274"},"observation_digest":"sha256:6d0a3ec770be422794d93fd7862d93ffaf3c64e52d8481d94a1c2adea45e765c","observation_id":"a1038bce-04a8-4705-bd47-0e6bff05cf57","resolution":{"observed_at":"2026-08-15T15:46:21.691185Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":"2109.04197","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-07-01T09:15:44.195185Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","venue":null,"work_id":"65d560ab-e9fb-4c4d-86f9-7037c08e0939","year":2021},"citing_paper":{"arxiv_id":"2604.24012","last_updated":"2026-06-09T08:27:40Z","snapshot_observed_at":"2026-08-12T21:23:16.599649Z","submitted_at":"2026-04-27T03:47:50Z","title":"FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-08T04:30:06.269559Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2604.24012"},"observation_digest":"sha256:02304930df700ee74f4038882a54cc50c3459e1505f8549354e5265c68234b6a","observation_id":"3cd6948d-2e7d-47fb-95e9-59eb2af836d0","resolution":{"observed_at":"2026-05-11T21:46:17.949087Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","version":1},"cited_work":{"arxiv_id":"2109.04197","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.04197","snapshot_observed_at":"2026-07-01T09:15:44.195185Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services","venue":null,"work_id":"65d560ab-e9fb-4c4d-86f9-7037c08e0939","year":2021},"citing_paper":{"arxiv_id":"2604.24012","last_updated":"2026-06-09T08:27:40Z","snapshot_observed_at":"2026-08-12T21:23:16.599649Z","submitted_at":"2026-04-27T03:47:50Z","title":"FedSLoP: Memory-Efficient Federated Learning with Low-Rank Gradient Projection","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-01T09:10:20.045403Z"},"links":{"cited_paper":"/paper/2109.04197","citing_paper":"/paper/2604.24012"},"observation_digest":"sha256:f970a557aae802302f1086c69dcba10ddd09266383eb011c963d0b156313021b","observation_id":"64bc6375-b7b6-4676-a87c-d0c7b128450b","resolution":{"observed_at":"2026-07-01T09:15:44.198715Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2109.04197/citation-record","integrity":"/paper/2109.04197/integrity","json":"/paper/2109.04197/citation-record.json","paper":"/paper/2109.04197"},"outbound":[],"paper":{"arxiv_id":"2109.04197","last_updated":"2021-09-09T12:09:53Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-18T01:09:22.015598Z","submitted_at":"2021-09-09T12:09:53Z","title":"A distillation-based approach integrating continual learning and federated learning for pervasive services"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2109.04197."}