{"as_of":"2026-08-15T05:37:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:54a1ff3e09508b7c90ac413ff60ae16c5831e3c8f15f3ea626ddf94c0ab48a62","coverage":[{"denominator":141,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T11:57:36.313408Z","state":"measured"},{"denominator":103,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":103,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T22:47:35.006814Z","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":"2026-07-02T19:47:18.791263Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"cited_work":{"arxiv_id":"1908.07873","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1908.07873","snapshot_observed_at":"2026-07-02T19:47:18.791263Z","title":"Federated learning: Challenges, methods, and future directions","venue":null,"work_id":"3f01aceb-57b1-4a93-89e7-7c6f196ac6df","year":1908},"citing_paper":{"arxiv_id":"2003.00295","last_updated":"2021-09-08T23:37:17Z","snapshot_observed_at":"2026-08-13T06:06:10.844945Z","submitted_at":"2020-02-29T16:37:29Z","title":"Adaptive Federated Optimization","version":5},"reference_index":225,"source":"arxiv_source","source_observed_at":"2026-05-21T10:30:58.601351Z"},"links":{"cited_paper":"/paper/1908.07873","citing_paper":"/paper/2003.00295"},"observation_digest":"sha256:1b03896bb5866f549d4da4504fa42ec83cf298c2b71800cad8bbf4cf0c1d455d","observation_id":"494f459a-4c39-4843-9461-23b8a7026464","resolution":{"observed_at":"2026-05-21T10:30:58.841023Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.07873","snapshot_observed_at":"2026-08-10T22:47:35.006814Z","title":"Federated learning: Challenges, methods, and future directions,","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2501.00732","last_updated":"2025-01-01T05:28:58Z","snapshot_observed_at":"2026-08-15T03:02:24.780189Z","submitted_at":"2025-01-01T05:28:58Z","title":"Gradient Compression and Correlation Driven Federated Learning for Wireless Traffic Prediction","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T22:47:35.006814Z"},"links":{"cited_paper":"/paper/1908.07873","citing_paper":"/paper/2501.00732"},"observation_digest":"sha256:a887b644f259219afaa286ee8f802af755baec7f820bafc8067cebd74f76b24a","observation_id":"e2326a4d-30e8-494c-9b7a-a777dfb8b7fa","resolution":{"observed_at":"2026-08-10T22:47:35.006814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"cited_work":{"arxiv_id":"1908.07873","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1908.07873","snapshot_observed_at":"2026-07-02T19:47:18.791263Z","title":"Federated learning: Challenges, methods, and future directions","venue":null,"work_id":"3f01aceb-57b1-4a93-89e7-7c6f196ac6df","year":1908},"citing_paper":{"arxiv_id":"2607.00173","last_updated":"2026-06-30T20:47:33Z","snapshot_observed_at":"2026-07-29T22:16:43.770651Z","submitted_at":"2026-06-30T20:47:33Z","title":"TallyTrain: Communication-Efficient Federated Distillation","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-07-02T19:44:47.733008Z"},"links":{"cited_paper":"/paper/1908.07873","citing_paper":"/paper/2607.00173"},"observation_digest":"sha256:1a03e110c5921e87e2a96351c711451d9b5aa7d4d791b7d5eb0f76ab19136478","observation_id":"c936e1be-f118-41e7-ae3a-6e018ace619a","resolution":{"observed_at":"2026-07-02T19:47:18.792734Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/1908.07873/citation-record","integrity":"/paper/1908.07873/integrity","json":"/paper/1908.07873/citation-record.json","paper":"/paper/1908.07873"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.933046Z","title":"URL https://www.tensorflow.org/federated","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.933046Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:c3c6499a005d5adbfb315c62e6805a5af8f53f1f9c58352cffc129ebd0de688c","observation_id":"b2955b72-0261-419a-a1f5-eddf9dcbc5c7","resolution":{"observed_at":"2026-08-14T11:57:35.933046Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.938293Z","title":"Abadi, A","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.938293Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:f53470ba5ab7811c9861b4877c9118beb00e863622336e8ab539125641d30fef","observation_id":"2989fb09-010d-41f2-938e-f444bcd7fcdd","resolution":{"observed_at":"2026-08-14T11:57:35.938293Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.942942Z","title":"Agarwal, A","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.942942Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:1b723d1d1f6094770557b3754195e2238ca6018b00ec248907d78971dee1db78","observation_id":"60389532-631d-4354-ad13-dfd06150bae4","resolution":{"observed_at":"2026-08-14T11:57:35.942942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.946687Z","title":"Agrawal and R","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.946687Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6beee389040360fa1cf6678d4e988abbfbf3ba9dc9b102d75b1feb3f2aa4a252","observation_id":"9536e541-37c6-4e30-ae4e-18a7e1257fcc","resolution":{"observed_at":"2026-08-14T11:57:35.946687Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.09888","last_updated":"2019-01-29T14:18:38Z","snapshot_observed_at":"2026-08-14T17:24:16.023139Z","submitted_at":"2019-01-29T14:18:38Z","title":"Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.09888","snapshot_observed_at":"2026-08-14T11:57:35.950581Z","title":"Ammad-ud din, E","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.950581Z"},"links":{"cited_paper":"/paper/1901.09888","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2fe6246470e982ab2d34898abca2eb0cff613b356f5af343dd0552dedeb75d3e","observation_id":"d54f832f-9ae6-45b8-9464-6965d01ac978","resolution":{"observed_at":"2026-08-14T11:57:35.950581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.954863Z","title":"Anguita, A","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.954863Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:cfec4a1b7f894856529803cb630b285c759a4684f73719e6389d8350855134be","observation_id":"0ebe6acc-d922-4264-8c0a-7c2f8d5db218","resolution":{"observed_at":"2026-08-14T11:57:35.954863Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.958860Z","title":"Bassily, A","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.958860Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:71eb0f822de387529e045e2bcdd92d0845ca3e62f4ba05d5ffe69d843d0a447d","observation_id":"bc2a9531-e4f6-4048-a3d8-732f2daad60e","resolution":{"observed_at":"2026-08-14T11:57:35.958860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.00984","last_updated":"2019-06-03T14:48:00Z","snapshot_observed_at":"2026-08-14T17:49:17.308567Z","submitted_at":"2018-12-03T18:59:16Z","title":"Protection Against Reconstruction and Its Applications in Private Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.00984","snapshot_observed_at":"2026-08-14T11:57:35.962840Z","title":"Bhowmick, J","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.962840Z"},"links":{"cited_paper":"/paper/1812.00984","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:cc152f39936bd8d20a3328bd158013c063a6f2983341dd041ae4c71898bac0c1","observation_id":"2914d106-4bde-431d-b43a-4084e449a710","resolution":{"observed_at":"2026-08-14T11:57:35.962840Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.966715Z","title":"Bolukbasi, J","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.966715Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:8dedd8fc5933e59d8ed0edfa80090c5031d3813c5b9d187729a3773eff10c444","observation_id":"22b59ac6-ab5a-4dcc-a799-b6ef1f9c4ac4","resolution":{"observed_at":"2026-08-14T11:57:35.966715Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.970057Z","title":"Bonawitz, V","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.970057Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:1df08dd99c7500c99cf2b1cf990ffb85822eead107fcfa363b12031b9625f078","observation_id":"6d09f09f-e283-42cc-aef2-1d2da2a85c47","resolution":{"observed_at":"2026-08-14T11:57:35.970057Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.973684Z","title":"Bonawitz, H","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.973684Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:1dd93f0875e4ec1cb84ab9be05b318fb9d247f22b684680c2c893fbb5eb5abbe","observation_id":"1d40715e-ec2b-431d-ba57-01baca8c3de9","resolution":{"observed_at":"2026-08-14T11:57:35.973684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.977200Z","title":"Bonomi, R","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.977200Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:020f543c9e4a83bbb670178235471a957153c84dc40ed5c9fb822baf95ee5923","observation_id":"0946d275-7b2a-4293-9776-773ddd827ba3","resolution":{"observed_at":"2026-08-14T11:57:35.977200Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.980627Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.980627Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2bbcbe20f2dfef1fc584265a068e9cf1168214f9ca6bdb137deb52bfabd81882","observation_id":"1a5af51f-51c9-4487-aa9f-8e0d43cd4909","resolution":{"observed_at":"2026-08-14T11:57:35.980627Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:35.984353Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.984353Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:4a74d861b17ba371b4626663d81329432069819e4e081406b12c97fe184c6ea2","observation_id":"4a26df15-88d6-47cf-ac04-9ac4190b2921","resolution":{"observed_at":"2026-08-14T11:57:35.984353Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.07210","last_updated":"2019-01-08T16:01:46Z","snapshot_observed_at":"2026-08-14T17:42:03.696369Z","submitted_at":"2018-12-18T07:31:18Z","title":"Expanding the Reach of Federated Learning by Reducing Client Resource Requirements","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.07210","snapshot_observed_at":"2026-08-14T11:57:35.987800Z","title":"Caldas, J","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.987800Z"},"links":{"cited_paper":"/paper/1812.07210","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6dfc93ef03dc0da725f6ca175367f0b6d11cd9a13e3adc28ef6917c38d25de5c","observation_id":"4066ab26-852b-4a19-90ac-fc546294358c","resolution":{"observed_at":"2026-08-14T11:57:35.987800Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.01097","last_updated":"2019-12-09T20:02:37Z","snapshot_observed_at":"2026-08-14T17:49:10.564747Z","submitted_at":"2018-12-03T21:59:41Z","title":"LEAF: A Benchmark for Federated Settings","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.01097","snapshot_observed_at":"2026-08-14T11:57:35.992157Z","title":"Caldas, P","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.992157Z"},"links":{"cited_paper":"/paper/1812.01097","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:3ebd7e29afeb4bfc75cec8e58d291a2ab3e46907603778440642183c540a545d","observation_id":"4466b572-099a-425d-a2f2-d55025b52be8","resolution":{"observed_at":"2026-08-14T11:57:35.992157Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.08232","last_updated":"2019-07-16T17:05:32Z","snapshot_observed_at":"2026-08-14T19:43:10.100538Z","submitted_at":"2018-02-22T18:42:41Z","title":"The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.08232","snapshot_observed_at":"2026-08-14T11:57:35.996660Z","title":"Carlini, C","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:35.996660Z"},"links":{"cited_paper":"/paper/1802.08232","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:786ca8846f2a4c7745354d3b9e0ab107e179cf36f3b55e9ca379c116bc2e1aef","observation_id":"267d95bd-43df-413d-8b14-c225c992a54c","resolution":{"observed_at":"2026-08-14T11:57:35.996660Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.000945Z","title":null,"venue":null,"work_id":null,"year":1997},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.000945Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0594f83e9f53895ac8958709d2af36ee9555ccd7be18e93d5afad0e7f9659bd1","observation_id":"8fd2c13f-242f-484d-9984-cef2b7dd8304","resolution":{"observed_at":"2026-08-14T11:57:36.000945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.004561Z","title":"Castro, B","venue":null,"work_id":null,"year":1999},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.004561Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:ebe329215f02ef830ead834a4e4736444c102d45168e9d019d10e47700cb9704","observation_id":"424421b8-b852-487e-8dc2-691644bc282c","resolution":{"observed_at":"2026-08-14T11:57:36.004561Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.008133Z","title":"Charles and D","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.008133Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:1d526f215a6d5dddc4c8dd326626bc2846280997a5c7be0e5223462bd6d97525","observation_id":"43c3bc33-80a2-4e05-a699-c4a1b064a06c","resolution":{"observed_at":"2026-08-14T11:57:36.008133Z","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":"1711.0677","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.880681Z","title":null,"venue":null,"work_id":"03af92eb-bcaf-4ae2-b968-d9353e178bb2","year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.011408Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:e2b338a666cba8311f068c6cae94bbd60a11d072abceca520b564cca4dbd89b8","observation_id":"d1afde38-0705-41bd-bec3-6cc42cca5f88","resolution":{"observed_at":"2026-08-14T11:57:36.886062Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:36.015135Z","title":"Chaudhuri, C","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.015135Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:3f51329a2fd0ebd7bc7788da1caf3876c9eb2bf174c6f549b62cc579bfebdc06","observation_id":"f8e81656-6e23-45c9-b49c-339368c0ffe3","resolution":{"observed_at":"2026-08-14T11:57:36.015135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.019448Z","title":null,"venue":null,"work_id":null,"year":1988},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.019448Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0c888ce29b1e840f7afbfc602e8bd0cffffb9f5d88fbc468b696430158140eb9","observation_id":"d16485f8-8b9f-42e7-91da-02426aff5cca","resolution":{"observed_at":"2026-08-14T11:57:36.019448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.07876","last_updated":"2019-12-14T06:39:54Z","snapshot_observed_at":"2026-08-14T19:43:29.400856Z","submitted_at":"2018-02-22T02:35:32Z","title":"Federated Meta-Learning with Fast Convergence and Efficient Communication","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.07876","snapshot_observed_at":"2026-08-14T11:57:36.022735Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.022735Z"},"links":{"cited_paper":"/paper/1802.07876","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:1f4d580cfc1a591794c998445619830664eea7e59d0a838ccb157f27d4b9b577","observation_id":"490e6733-60e6-4e91-beb0-5b11d2cf5bae","resolution":{"observed_at":"2026-08-14T11:57:36.022735Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.00329","last_updated":"2019-01-02T11:50:14Z","snapshot_observed_at":"2026-08-14T17:36:00.574325Z","submitted_at":"2019-01-02T11:50:14Z","title":"Secure Computation for Machine Learning With SPDZ","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.00329","snapshot_observed_at":"2026-08-14T11:57:36.026565Z","title":null,"venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.026565Z"},"links":{"cited_paper":"/paper/1901.00329","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:49a01ae3123362420bd0197963e3624de790b0740f61ee0342cdb63f4d222318","observation_id":"0845d26c-0c23-44f0-85bb-5df1a80664e8","resolution":{"observed_at":"2026-08-14T11:57:36.026565Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.06268","last_updated":"2021-02-04T14:38:06Z","snapshot_observed_at":"2026-08-14T16:15:29.643635Z","submitted_at":"2019-06-14T16:09:56Z","title":"Variational Federated Multi-Task Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.06268","snapshot_observed_at":"2026-08-14T11:57:36.030449Z","title":"Corinzia and J","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.030449Z"},"links":{"cited_paper":"/paper/1906.06268","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:effd0ea043e286bca195f5d7ec2c57989cfe8f0fef6d71c6eb7d5d8f3786b5a8","observation_id":"7c39854b-f47b-457b-9b7c-878d54ad1c80","resolution":{"observed_at":"2026-08-14T11:57:36.030449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.034083Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.034083Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:523585cdcd2b53f39e15f88a5f6569442131fe1fe75cb2df8a9cb0cbbd495d38","observation_id":"c9ba3d8a-3480-4107-8016-f88b50c8794d","resolution":{"observed_at":"2026-08-14T11:57:36.034083Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.038059Z","title":"Dekel, R","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.038059Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:a139a7c8ad1813166ebc1feb33802d794aac65bf4976de2e54087a4c61448fd5","observation_id":"a976053d-cfa0-4cd7-a65a-b7c62a1646ed","resolution":{"observed_at":"2026-08-14T11:57:36.038059Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.041845Z","title":"Deshpande, C","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.041845Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:f0456d773db5bf9f265e07e823b6a59f824d589dcb2268fe2a50b9907adeed50","observation_id":"b6ad941b-760e-4b16-b14d-1b4caf983147","resolution":{"observed_at":"2026-08-14T11:57:36.041845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.045972Z","title":"Duchi, M","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.045972Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:474e2fcd7b942a7483dd561a20b2b0c3dc5996f3cfbdb952aa4bf1871688d088","observation_id":"58cbd7cf-5827-4cb2-a7c8-545938b7e6e0","resolution":{"observed_at":"2026-08-14T11:57:36.045972Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.050025Z","title":null,"venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.050025Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:b5b5c5fe495a40aff4daff216492fe5a4a6837512d61c29e42f6681b41f57a47","observation_id":"17421600-06df-4303-aec6-a20c9a0999c4","resolution":{"observed_at":"2026-08-14T11:57:36.050025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.053897Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.053897Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2a2925364b1571961bd246c3b17813f4394dca2c2a022d3c961f56ab7e2452d5","observation_id":"0a1f68b8-0cb1-4126-862c-9dac0cd71fc5","resolution":{"observed_at":"2026-08-14T11:57:36.053897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.058148Z","title":"Dwork and A","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.058148Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:f9f886e097794be5077aeefd47d8cf8d7a3a149459804c29f21f0bef1b3367b0","observation_id":"ba503359-4e0b-4874-a87a-a775413d5f30","resolution":{"observed_at":"2026-08-14T11:57:36.058148Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.061704Z","title":"Dwork, F","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.061704Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:9880534779f341ad705c8f08d62492a0cfa294541da7059d97a109eb3a914bb4","observation_id":"fe0f3ee5-2d96-4fe4-9c63-f8bb41b87905","resolution":{"observed_at":"2026-08-14T11:57:36.061704Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.065955Z","title":"Eichner, T","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.065955Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:93f96d21d62cfd91d0b1367d8382ca1fc0488fbd8104bfebfde7ce4eccab0a1f","observation_id":"c61d1796-f073-4c4f-8ced-dd03e3d98f11","resolution":{"observed_at":"2026-08-14T11:57:36.065955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.069927Z","title":"El Emam and F","venue":null,"work_id":null,"year":2008},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.069927Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:3f449e4c189e3eb54593eb0252233ae4f2e366877ccee13491169183ce57a43e","observation_id":"8c84a5dc-75fd-458a-a8bb-7d4be1766d4a","resolution":{"observed_at":"2026-08-14T11:57:36.069927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.073789Z","title":"Evgeniou and M","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.073789Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:c0bbe75159aa8d6c01960726c62c4dc5e0a4e9a88969d83c5a92184d8dba3d3b","observation_id":"f4b525d0-7006-4be7-b66b-05f2a5efb75f","resolution":{"observed_at":"2026-08-14T11:57:36.073789Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.077502Z","title":"Feldman, I","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.077502Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:209a34b96eb5735426f1dceda689d0c7da14ac5995e54d5ba242e620f78c26cd","observation_id":"852817a0-c9ed-43a4-9768-ffc07850f8f8","resolution":{"observed_at":"2026-08-14T11:57:36.077502Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.081609Z","title":"Fredrikson, S","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.081609Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:5304b7f410086eed43247e7fe1d850a05042efba606bf04999312a9c688ffe0f","observation_id":"7e7ea2e1-779e-40a7-81e7-6a5c3176e936","resolution":{"observed_at":"2026-08-14T11:57:36.081609Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.085473Z","title":"Garcia Lopez, A","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.085473Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:3b093e86ff657c2ccd81f1d6f7279dc68bbbe269dd75ca9f441550eb1665227b","observation_id":"f9427ccc-858d-4a53-b8b3-d0cace576bad","resolution":{"observed_at":"2026-08-14T11:57:36.085473Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1712.07557","last_updated":"2018-03-01T10:12:27Z","snapshot_observed_at":"2026-08-14T20:01:37.630399Z","submitted_at":"2017-12-20T16:28:37Z","title":"Differentially Private Federated Learning: A Client Level Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.07557","snapshot_observed_at":"2026-08-14T11:57:36.089447Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.089447Z"},"links":{"cited_paper":"/paper/1712.07557","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:ee365c62a4d5a6579333ddd91e78689b2f17d9f83a2224b3d481d0e843626084","observation_id":"d15023b4-284e-4d53-8306-774dcdb8afaa","resolution":{"observed_at":"2026-08-14T11:57:36.089447Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1906.08320","last_updated":"2019-12-02T17:53:21Z","snapshot_observed_at":"2026-08-15T03:42:43.033480Z","submitted_at":"2019-06-19T19:30:05Z","title":"Scalable and Differentially Private Distributed Aggregation in the Shuffled Model","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.08320","snapshot_observed_at":"2026-08-14T11:57:36.094013Z","title":"Ghazi, R","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.094013Z"},"links":{"cited_paper":"/paper/1906.08320","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:03847a8663b8ddaeb861c6acd197236b49eabca51d2279fe0a28ec07c522f402","observation_id":"8ffa1c18-8d12-4cde-91ed-515fc1fd9ff2","resolution":{"observed_at":"2026-08-14T11:57:36.094013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.099364Z","title":"Goryczka and L","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.099364Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:5327970356feac8becec7ec68e513dd73df9083ceb4fce0ebac5884cdef8e8ae","observation_id":"5cd6cc37-f260-4bcd-9649-62872a68473b","resolution":{"observed_at":"2026-08-14T11:57:36.099364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1805.07782","last_updated":"2019-06-04T18:34:56Z","snapshot_observed_at":"2026-08-14T19:13:15.173113Z","submitted_at":"2018-05-20T15:58:14Z","title":"Model Aggregation via Good-Enough Model Spaces","version":3},"cited_work":{"arxiv_id":"1805.07782","doi":null,"metadata_source":"pith","pith_arxiv_id":"1805.07782","snapshot_observed_at":"2026-08-14T11:57:36.741651Z","title":"Model Aggregation via Good-Enough Model Spaces","venue":"cs.LG","work_id":"334adb63-5827-46aa-a52e-a1cd4d1a4a65","year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.103449Z"},"links":{"cited_paper":"/paper/1805.07782","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2fc17249a7e171600bb853b9595108c1ff6aa88b8afd5f0856e1879d6b9404b2","observation_id":"fe22140d-db45-455e-9b7c-4ed4873e2714","resolution":{"observed_at":"2026-08-14T11:57:36.745767Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.11175","last_updated":"2019-03-05T20:33:39Z","snapshot_observed_at":"2026-08-14T17:09:33.713887Z","submitted_at":"2019-02-28T15:55:18Z","title":"One-Shot Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.11175","snapshot_observed_at":"2026-08-14T11:57:36.107494Z","title":null,"venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.107494Z"},"links":{"cited_paper":"/paper/1902.11175","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:d17c2dff270936fb8a276ec4529600096507516db24a4d9df634c16499a1af96","observation_id":"cda7b228-46bc-4142-9c14-db424c4446b5","resolution":{"observed_at":"2026-08-14T11:57:36.107494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.03604","last_updated":"2019-02-28T21:07:51Z","snapshot_observed_at":"2026-08-15T01:02:23.645244Z","submitted_at":"2018-11-08T18:37:03Z","title":"Federated Learning for Mobile Keyboard Prediction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.03604","snapshot_observed_at":"2026-08-14T11:57:36.111471Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.111471Z"},"links":{"cited_paper":"/paper/1811.03604","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:a54913fc9f45415c7b6c0a6115572803688a55076efd5ff1cd30b34a0fd7964b","observation_id":"5d31cecd-482e-4deb-86a9-8af363269930","resolution":{"observed_at":"2026-08-14T11:57:36.111471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.115516Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.115516Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:77adf26ca03be46ca7dab8765b7121288a9f78966b680234389367c55f1cdbb0","observation_id":"92eeebe2-1a71-4f6d-8951-7e993a96ee72","resolution":{"observed_at":"2026-08-14T11:57:36.115516Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.119168Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.119168Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:f924caa00b68822c4507d858f4cd286f3697a3b3980135cc28ebd3fc2177cab2","observation_id":"d344b979-2aac-43ee-a70e-c20a76747142","resolution":{"observed_at":"2026-08-14T11:57:36.119168Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.122950Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.122950Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:8012a4b21c231dd08d6f854625c504dfbcda5a98c33b2e44dae25a8b30ecbf71","observation_id":"1ac3e5fd-0cfa-42a2-ab4d-bb89915e5774","resolution":{"observed_at":"2026-08-14T11:57:36.122950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.126712Z","title":"Huang, F","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.126712Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:7822780619eb772916e9970809f493cd68d2e7e5feabd1a32bfaca2bb7a81018","observation_id":"a6758dee-3da0-4185-92e6-c6fc2a839c54","resolution":{"observed_at":"2026-08-14T11:57:36.126712Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1903.09296","last_updated":"2019-03-22T01:49:30Z","snapshot_observed_at":"2026-08-14T16:58:29.498195Z","submitted_at":"2019-03-22T01:49:30Z","title":"Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records","version":1},"cited_work":{"arxiv_id":"1903.09296","doi":null,"metadata_source":"pith","pith_arxiv_id":"1903.09296","snapshot_observed_at":"2026-08-14T11:57:36.707426Z","title":"Patient Clustering Improves Efficiency of Federated Machine Learning to predict mortality and hospital stay time using distributed Electronic Medical Records","venue":"cs.LG","work_id":"ad65a02d-eef4-4016-8793-6c2176f2338e","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.131454Z"},"links":{"cited_paper":"/paper/1903.09296","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:b0cadf8bbc7f8e6363684578d643a70b7b2d893baf99044b5e497331f60243d2","observation_id":"d2c699c8-1cf6-4888-9680-3f894d071017","resolution":{"observed_at":"2026-08-14T11:57:36.711481Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.12629","last_updated":"2020-08-12T06:14:13Z","snapshot_observed_at":"2026-08-14T17:50:50.284748Z","submitted_at":"2018-11-30T06:05:21Z","title":"LoAdaBoost: loss-based AdaBoost federated machine learning with reduced computational complexity on IID and non-IID intensive care data","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.12629","snapshot_observed_at":"2026-08-14T11:57:36.135995Z","title":"Huang, Y","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.135995Z"},"links":{"cited_paper":"/paper/1811.12629","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6a12d6707d3d1f3a4267a9131bbfb44fd0f1656fe00fddcef67985cbd057fe95","observation_id":"eac7a29c-71a8-4e82-8ea9-459b6bd5034c","resolution":{"observed_at":"2026-08-14T11:57:36.135995Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.140213Z","title":"Iyengar, J","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.140213Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:629089e39fa36be75b0c3c50c3bdb9191fb2b43cdce000ed5c56a2c882b5593b","observation_id":"aed4b3bd-622b-4ca9-8af9-339ced3d9755","resolution":{"observed_at":"2026-08-14T11:57:36.140213Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.143712Z","title":"Jaggi, V","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.143712Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:29ed5970623cc85e9af9f8d81d393bbc1ac33a1b88f5985af5a9eade3612f669","observation_id":"6e478793-7ed4-4177-8e46-4204c520e99a","resolution":{"observed_at":"2026-08-14T11:57:36.143712Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1811.11479","last_updated":"2023-10-19T14:11:11Z","snapshot_observed_at":"2026-08-14T17:52:08.881217Z","submitted_at":"2018-11-28T10:16:18Z","title":"Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1811.11479","snapshot_observed_at":"2026-08-14T11:57:36.147010Z","title":"Jeong, S","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.147010Z"},"links":{"cited_paper":"/paper/1811.11479","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0daaecc81a53ec8b2a0e0801e32368b3fcbd83730ae8a5be2cfc1cfaa2818b93","observation_id":"9d4068a9-d181-49c1-9007-59a6408ccec1","resolution":{"observed_at":"2026-08-14T11:57:36.147010Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.150448Z","title":"Jiang and G","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.150448Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:7c38ba58760c9eaa9ff1bb89d0257d6a7712dced039bd2eab9494b2f284c4668","observation_id":"eaa53c08-c265-4849-91b6-d25b4a2915ab","resolution":{"observed_at":"2026-08-14T11:57:36.150448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.07479","last_updated":"2019-10-24T12:13:23Z","snapshot_observed_at":"2026-08-14T16:31:19.852521Z","submitted_at":"2019-05-16T10:50:19Z","title":"Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach","version":2},"cited_work":{"arxiv_id":"1905.07479","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.07479","snapshot_observed_at":"2026-08-14T11:57:36.674161Z","title":"Incentive Design for Efficient Federated Learning in Mobile Networks: A Contract Theory Approach","venue":"cs.LG","work_id":"9b60e654-eb99-4581-b0f2-07a96b3e1038","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.153902Z"},"links":{"cited_paper":"/paper/1905.07479","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:4b37da87c77e48d2a4496620ddf8e451d54d65f9ac3b69e61be3eb867d3f3f8b","observation_id":"687d24f2-5c6c-4ae2-a271-00943091458b","resolution":{"observed_at":"2026-08-14T11:57:36.678882Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.02717","last_updated":"2019-12-07T03:50:47Z","snapshot_observed_at":"2026-08-14T16:19:41.413011Z","submitted_at":"2019-06-06T17:36:34Z","title":"Adaptive Gradient-Based Meta-Learning Methods","version":3},"cited_work":{"arxiv_id":"1906.02717","doi":null,"metadata_source":"pith","pith_arxiv_id":"1906.02717","snapshot_observed_at":"2026-08-14T11:57:36.659881Z","title":"Adaptive Gradient-Based Meta-Learning Methods","venue":"cs.LG","work_id":"5c284ab5-84a0-4a96-8f28-19cd01db38f6","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.157541Z"},"links":{"cited_paper":"/paper/1906.02717","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0e2ce6569bcf86186feb405e3c3a54a9a2aa3a5b037b34443cd9a3942b303eff","observation_id":"1e875a4d-10af-4327-8c2e-460bce95b5ea","resolution":{"observed_at":"2026-08-14T11:57:36.663830Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.05492","last_updated":"2017-10-30T20:52:14Z","snapshot_observed_at":"2026-08-13T17:19:46.488095Z","submitted_at":"2016-10-18T09:11:51Z","title":"Federated Learning: Strategies for Improving Communication Efficiency","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.05492","snapshot_observed_at":"2026-08-14T11:57:36.161150Z","title":"Koneˇ cn`y, H","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.161150Z"},"links":{"cited_paper":"/paper/1610.05492","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:bbce730bdf94169c2d5c718019658e39580c5ce85bef94d9ceedcf6c98d96beb","observation_id":"6a1a4b47-0c2a-4808-bb99-b31f7c9c488f","resolution":{"observed_at":"2026-08-14T11:57:36.161150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.165025Z","title":"Kuflik, J","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.165025Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:66204c72948b105cd7d1e9532f2767cc32b4f4687f162a43c5b4653304ecb3b2","observation_id":"c6ba3e49-832c-4404-9bba-e4f2acf8239e","resolution":{"observed_at":"2026-08-14T11:57:36.165025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10466","last_updated":"2019-05-24T22:29:57Z","snapshot_observed_at":"2026-08-14T16:26:51.197893Z","submitted_at":"2019-05-24T22:29:57Z","title":"Decentralized Bayesian Learning over Graphs","version":1},"cited_work":{"arxiv_id":"1905.10466","doi":null,"metadata_source":"pith","pith_arxiv_id":"1905.10466","snapshot_observed_at":"2026-08-14T11:57:36.636147Z","title":"Decentralized Bayesian Learning over Graphs","venue":"stat.ML","work_id":"fb9624d6-9a41-49ac-aaed-17580c7c5ce6","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.168510Z"},"links":{"cited_paper":"/paper/1905.10466","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:529971b80314d1692827c97105c3b813fe41c97b995c705a9e3c89a0b9bd878a","observation_id":"3cf188e6-821d-4666-9c28-1dfff837893c","resolution":{"observed_at":"2026-08-14T11:57:36.640070Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:36.172049Z","title":"Lee and D","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.172049Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:d1829608a6f276540dcdddb6bc630a711afa991ef1117961ef1c59a6cd91aa97","observation_id":"71ca5ac6-3b14-4d0c-9b35-fa01d2137eb1","resolution":{"observed_at":"2026-08-14T11:57:36.172049Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.175264Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.175264Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:8a9e443745fd06af9c0fd3e4b6f5f76f7f5f9d7bafd453e6d7277f796f226c0a","observation_id":"f9cc0a13-5be7-4514-b5dc-a7954773f85c","resolution":{"observed_at":"2026-08-14T11:57:36.175264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.178539Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.178539Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:ac8eafd2845b6a5346aca58e37cbe60d54e8e00ec60864628f10916f14fc91a5","observation_id":"fa70bf92-543c-46f8-ad5c-09c99f39009e","resolution":{"observed_at":"2026-08-14T11:57:36.178539Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.06127","last_updated":"2020-04-21T18:58:23Z","snapshot_observed_at":"2026-08-15T01:11:14.928056Z","submitted_at":"2018-12-14T19:28:29Z","title":"Federated Optimization in Heterogeneous Networks","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.06127","snapshot_observed_at":"2026-08-14T11:57:36.181970Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.181970Z"},"links":{"cited_paper":"/paper/1812.06127","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2e00005eabf0bac49aa175d912e0a5dc5b04e505d76761cdba4458784defe412","observation_id":"6926bd58-099f-446c-a6e2-d8d8399f2f8f","resolution":{"observed_at":"2026-08-14T11:57:36.181970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10497","last_updated":"2020-02-14T22:48:28Z","snapshot_observed_at":"2026-08-14T16:26:48.571116Z","submitted_at":"2019-05-25T01:47:41Z","title":"Fair Resource Allocation in Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10497","snapshot_observed_at":"2026-08-14T11:57:36.185885Z","title":null,"venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.185885Z"},"links":{"cited_paper":"/paper/1905.10497","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:c859e3a72764a4b88e46e34cf3a847104dc1c7b767176baf45e69958231ab201","observation_id":"5553a780-a77a-4813-ba1d-be1298f3a251","resolution":{"observed_at":"2026-08-14T11:57:36.185885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.189552Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.189552Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:115ccbb2ec2775c43046e34f5cd8e091118502277d18f3e5d7e2dbf1edc7ff79","observation_id":"0cf5784a-4f5f-4c05-bb18-3c9d6b997623","resolution":{"observed_at":"2026-08-14T11:57:36.189552Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.07217","last_updated":"2020-02-17T11:42:10Z","snapshot_observed_at":"2026-08-14T18:38:32.170609Z","submitted_at":"2018-08-22T04:50:55Z","title":"Don't Use Large Mini-Batches, Use Local SGD","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.07217","snapshot_observed_at":"2026-08-14T11:57:36.192943Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.192943Z"},"links":{"cited_paper":"/paper/1808.07217","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:be6229c41b34931f8e80874aa54997d8646d3dd5facbd3b6025a9b1f9954436c","observation_id":"17a061b5-338b-4b9a-b1ed-53ba7dfc0f58","resolution":{"observed_at":"2026-08-14T11:57:36.192943Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.196616Z","title":"Lindell and B","venue":null,"work_id":null,"year":2000},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.196616Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6bbdc558851ad2648c239481f981a78e4169da8bc8d67355f5a0fd882b6c33a1","observation_id":"662de79c-7b74-4d9e-9576-5597ca6829d9","resolution":{"observed_at":"2026-08-14T11:57:36.196616Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.06641","last_updated":"2019-10-31T14:45:01Z","snapshot_observed_at":"2026-08-14T16:31:20.477466Z","submitted_at":"2019-05-16T10:23:36Z","title":"Client-Edge-Cloud Hierarchical Federated Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.06641","snapshot_observed_at":"2026-08-14T11:57:36.200025Z","title":null,"venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.200025Z"},"links":{"cited_paper":"/paper/1905.06641","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:cc3b3862c18697f8c4e5bb5f2a0ae733f4486f1dc564b8fa04399f3e0e09f770","observation_id":"7656c601-4fd8-4b24-8b75-9f54a384ce07","resolution":{"observed_at":"2026-08-14T11:57:36.200025Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.203586Z","title":null,"venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.203586Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:96035e590557604266c42034060a113ceceb9af769caca9f2929b1bcd84a9a0c","observation_id":"8360c415-7f31-46f5-9298-89adda36de58","resolution":{"observed_at":"2026-08-14T11:57:36.203586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.207156Z","title":null,"venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.207156Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:497d79c603f8d73602fdf44105b6194b359dd3589bf18b8f43824c559c010aa3","observation_id":"c9b8e75d-ba56-41c9-947d-a15ac6d411b6","resolution":{"observed_at":"2026-08-14T11:57:36.207156Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.210851Z","title":null,"venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.210851Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:170808cb22d5293c13c4a5a72a2b6536839d22e00e71bdbba7fe753726186347","observation_id":"e75c71eb-bc6c-4344-8de5-f7bc50a40352","resolution":{"observed_at":"2026-08-14T11:57:36.210851Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.214339Z","title":null,"venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.214339Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:8d08dfe87c6389a1483e692b2d9378323405b4e44e1452aa116fe9ddac585758","observation_id":"80c51dec-095a-45b4-a10d-195232a60c4a","resolution":{"observed_at":"2026-08-14T11:57:36.214339Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.218260Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.218260Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:bb7e1d5c085b90f85b481d7a79ac34dcc3ca1fbbece7ead797d3f77d962e2621","observation_id":"13c70fdb-a3b2-453c-8c1f-d78f9d85107e","resolution":{"observed_at":"2026-08-14T11:57:36.218260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.223059Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.223059Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:fb25fd49f14ecb1b527497dcf8210f1081fbf3e2425c108bfebf24752b26350d","observation_id":"ea83c5f1-af50-46bd-b7f8-51d4abd480a4","resolution":{"observed_at":"2026-08-14T11:57:36.223059Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.226936Z","title":"Melis, G","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.226936Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6cbbda674a4b8abc4ea295b359a16913eb8155d97205f23d9baf911e560b514b","observation_id":"14dc6466-8e94-4f15-86b9-76ec63d77879","resolution":{"observed_at":"2026-08-14T11:57:36.226936Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.230564Z","title":"Melis, C","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.230564Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:d58c99b19532d3a2e7f65234027bd5410e9a1dbd4dc07a2b05602844a7c1a650","observation_id":"20291f6d-0668-4b82-bf73-80cd4991aa4e","resolution":{"observed_at":"2026-08-14T11:57:36.230564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.234152Z","title":"Mohassel and P","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.234152Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:bb09fde74e3b544de95866deaf9f5befe825cbd3a85ba5ffa9d3290dbfb11769","observation_id":"ae2022ab-c378-49c9-ab70-257ed25d3178","resolution":{"observed_at":"2026-08-14T11:57:36.234152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.237775Z","title":"Mohri, G","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.237775Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:5461b0d8b790f9d23384811d775a6f03e9a463f2c6c0368b021f3b30f78c041f","observation_id":"7f594eb1-8000-4058-8035-8f818821f649","resolution":{"observed_at":"2026-08-14T11:57:36.237775Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.241524Z","title":null,"venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.241524Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:26c712dea783b1864c299040c28d9b3583fc5cc3eb4c2f1bbe424c31b2a46b17","observation_id":"b6ef0a42-c300-4d66-8b03-2fb7fe2a8031","resolution":{"observed_at":"2026-08-14T11:57:36.241524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.244842Z","title":"Nikolaenko, U","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.244842Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:e99ee0129c2ebece2ff0b5261b4c8e674b53d1e3c3abcf433069a358212d62eb","observation_id":"4bc52b20-419f-4572-b52d-e703286d1ba2","resolution":{"observed_at":"2026-08-14T11:57:36.244842Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.248408Z","title":"Nishio and R","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.248408Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:a720b0f0422bd0734bf0e182e82dd334b7224d6b778b08140e23249c67b3ba45","observation_id":"dbeb0b22-2fbb-45d6-afb2-49ec5dc33688","resolution":{"observed_at":"2026-08-14T11:57:36.248408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.251934Z","title":"Pantelopoulos and N","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.251934Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:8873a5e1d0b1d9e798d94fe6c9aab91fc666e39c1af779294fa83bad69e85b76","observation_id":"6e928574-0705-4626-89b1-84bb25eee5b6","resolution":{"observed_at":"2026-08-14T11:57:36.251934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.255315Z","title":"Papernot, M","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.255315Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:6ae0a85a0a546c78f0d2d9d5f9b3ab173f33ba632f75432d9fc36eb34ebe5f73","observation_id":"ed9eaaa6-585d-40c2-906c-0d469570b02b","resolution":{"observed_at":"2026-08-14T11:57:36.255315Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T11:57:36.258925Z","title":"Papernot, S","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.258925Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:cae556aa1aff158960b3eec14bc0e5d9e7ff9ea9f8edc577727000c2d91f2a7f","observation_id":"d36527f8-45b0-45cd-bcb7-469e9d18f816","resolution":{"observed_at":"2026-08-14T11:57:36.258925Z","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":"2026-08-14T11:57:37.392969Z","title":null,"venue":null,"work_id":"85d7513e-da39-4043-84e8-8181e0e68352","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.262269Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:65cc2fe4a2f14881aece035fd17f512cdf2b95de2798c1312f6ce7f9746f7798","observation_id":"32d8eca9-5a53-4e7b-8888-9b7472283091","resolution":{"observed_at":"2026-08-14T11:57:37.396264Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:37.383297Z","title":null,"venue":null,"work_id":"6fec34f0-0434-4123-b46d-d3d26aebca0c","year":2015},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.266549Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:a33d45be6e65c641d72decfbedbeb08951c88ef8fed4d7732fc81afb2bdee092","observation_id":"e91b486c-5807-4c72-b275-67ec46ee1812","resolution":{"observed_at":"2026-08-14T11:57:37.386546Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1906.04329","last_updated":"2019-06-11T00:40:33Z","snapshot_observed_at":"2026-08-14T16:17:46.958887Z","submitted_at":"2019-06-11T00:40:33Z","title":"Federated Learning for Emoji Prediction in a Mobile Keyboard","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1906.04329","snapshot_observed_at":"2026-08-14T11:57:36.270811Z","title":"Ramaswamy, R","venue":null,"work_id":null,"year":1906},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.270811Z"},"links":{"cited_paper":"/paper/1906.04329","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:b7605c4f62502ca410005032325dcd4c9a6482951dd10f061e7537ed156993c8","observation_id":"5e2d0f71-eca3-4352-bd03-62bece8d5879","resolution":{"observed_at":"2026-08-14T11:57:36.270811Z","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":"2026-08-14T11:57:37.372819Z","title":"Rastegari, V","venue":null,"work_id":"38c5a70b-8d40-41b0-b39f-25665132bf9a","year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.274627Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0bbad9a10a139c3dff77d99608e6303b1de1295bec6daed629c4a1b6788267a8","observation_id":"030a2c94-561e-4c7c-b951-4192d01f54ce","resolution":{"observed_at":"2026-08-14T11:57:37.377170Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.03257","last_updated":"2019-12-01T20:27:06Z","snapshot_observed_at":"2026-08-14T16:54:49.406711Z","submitted_at":"2019-03-29T12:43:36Z","title":"MLSys: The New Frontier of Machine Learning Systems","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.03257","snapshot_observed_at":"2026-08-14T11:57:36.278976Z","title":"Ratner et al","venue":null,"work_id":null,"year":1904},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.278976Z"},"links":{"cited_paper":"/paper/1904.03257","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:dcd8b3caba7baad4efef828dead2209e1ac6b441b3fdfdac11e47f1537028eec","observation_id":"5e97a3eb-a042-4280-930b-ae97dbd2fc0a","resolution":{"observed_at":"2026-08-14T11:57:36.278976Z","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":"2026-08-14T11:57:37.363085Z","title":"Recht, C","venue":null,"work_id":"7fba52c3-c97b-484a-9843-55b4a44d4495","year":2011},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.282521Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:fe2bca45c4fa64ea35785ae30d11cf8fd15b39553492a008fa4a8d31c29a03a2","observation_id":"deb2a656-c0de-42db-9e82-a796a0f990bc","resolution":{"observed_at":"2026-08-14T11:57:37.366511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.06879","last_updated":"2016-08-24T16:04:12Z","snapshot_observed_at":"2026-08-14T21:42:57.169954Z","submitted_at":"2016-08-24T16:04:12Z","title":"AIDE: Fast and Communication Efficient Distributed Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.06879","snapshot_observed_at":"2026-08-14T11:57:36.285988Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.285988Z"},"links":{"cited_paper":"/paper/1608.06879","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:ffdf57a8f8e42dea1e1c8bd734166d7a5daad4b262a53d14aa4d54421756ff91","observation_id":"20da5d03-5591-4cf9-88e1-bb396127ef06","resolution":{"observed_at":"2026-08-14T11:57:36.285988Z","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":"2026-08-14T11:57:37.353960Z","title":"Reisizadeh, S","venue":null,"work_id":"8667bc71-51f2-4c91-9112-1380f66bea18","year":2019},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.289679Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:917bb3aaabfa095cefaf0412d38fa7cdfc369c4f97d987ebdc23705e28084092","observation_id":"3c410d11-3dd2-4bd2-976e-ef04d43097e6","resolution":{"observed_at":"2026-08-14T11:57:37.357084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:37.343937Z","title":null,"venue":null,"work_id":"9b583f6e-d17d-4abc-b7c3-afd639a9b5ec","year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.293977Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:0e138c4c93676229345aecd136d2e828611c93112d2fd30fce6da9be20460f8e","observation_id":"6d3c7680-566e-4821-884e-01bf74d1bb92","resolution":{"observed_at":"2026-08-14T11:57:37.347240Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:37.333672Z","title":"Richtárik and M","venue":null,"work_id":"3940146c-6adc-431d-93c1-512920b2f131","year":2016},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.297098Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:99ffc666c7d545fc246010226c59c748eb452d0ecad6f17be960359d61885bda","observation_id":"f68a12f3-0f51-4dd8-878c-b4c2f82178e5","resolution":{"observed_at":"2026-08-14T11:57:37.337385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:37.323853Z","title":null,"venue":null,"work_id":"e5796392-0c46-4b03-aef0-f0184540197f","year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.300615Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:bfa91ea85e3fdc54449f924cbcc8f45719265efa302955650f1bc31f63c5399e","observation_id":"8eaf8df7-17e5-4608-9bef-2afe44b07743","resolution":{"observed_at":"2026-08-14T11:57:37.327223Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-14T11:57:37.313888Z","title":"Samarakoon, M","venue":null,"work_id":"f6e1a8f2-5e78-494b-a705-4e98d360c183","year":2018},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.304272Z"},"links":{"citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:2c4eea07bb5d2ceddab5154420039a472ca97406a1377c26b15539cfaec51a06","observation_id":"70f98749-2cbe-4262-bb56-1669381de0ae","resolution":{"observed_at":"2026-08-14T11:57:37.317351Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1903.02891","last_updated":"2019-03-07T13:10:30Z","snapshot_observed_at":"2026-08-14T17:05:57.007398Z","submitted_at":"2019-03-07T13:10:30Z","title":"Robust and Communication-Efficient Federated Learning from Non-IID Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1903.02891","snapshot_observed_at":"2026-08-14T11:57:36.308744Z","title":"Sattler, S","venue":null,"work_id":null,"year":1903},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.308744Z"},"links":{"cited_paper":"/paper/1903.02891","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:cdeea8d37504ade4d3d7fefb85cd9c31c5cc2fe8f5d00e1c9e99c574156c6092","observation_id":"6704a0fb-b0ba-48f8-9a0c-f43d55123b98","resolution":{"observed_at":"2026-08-14T11:57:36.308744Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1308.6370","last_updated":"2013-08-29T06:06:42Z","snapshot_observed_at":"2026-08-15T00:05:07.251336Z","submitted_at":"2013-08-29T06:06:42Z","title":"Fast Convergence of Stochastic Gradient Descent under a Strong Growth Condition","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1308.6370","snapshot_observed_at":"2026-08-14T11:57:36.313408Z","title":"Schmidt and N","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-14T11:57:36.313408Z"},"links":{"cited_paper":"/paper/1308.6370","citing_paper":"/paper/1908.07873"},"observation_digest":"sha256:49d5553cd0fa2e2d54095ab448965e760bdac1f54fe5a98c44917d7b33d93d1d","observation_id":"48724cc3-c544-4a56-af6e-601597734853","resolution":{"observed_at":"2026-08-14T11:57:36.313408Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"1908.07873","last_updated":"2019-08-21T13:53:23Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T00:39:13.596858Z","submitted_at":"2019-08-21T13:53:23Z","title":"Federated Learning: Challenges, Methods, and Future Directions"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":89,"verified_exact":6,"verified_fuzzy":5},"total_outbound_references":141},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 100 of 141 outbound references and 3 inbound Pith citation observations for arXiv:1908.07873."}