{"as_of":"2026-08-05T15:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f808dc00f80c7a126e1c99f2e1c395ca42e5676cbceb0aa33654e90fb25cff78","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-25T17:17:45.029352Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/1906.10546/citation-record","integrity":"/paper/1906.10546/integrity","json":"/paper/1906.10546/citation-record.json","paper":"/paper/1906.10546"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A theory of learning from different domains","venue":null,"work_id":"752208da-7176-41ca-85a0-1ee8bda4c454","year":2010},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:4f7c707646985108a334520d1ef7fa5199cbf8876f0cdc9f0a32cef7494420ef","observation_id":"e7cdf089-3d25-4d07-912a-568470a0c9e2","resolution":{"observed_at":"2026-05-25T17:21:06.083533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.07698","last_updated":"2022-09-04T16:26:45Z","snapshot_observed_at":"2026-08-05T14:58:26.973581Z","submitted_at":"2018-01-23T18:39:19Z","title":"ArcFace: Additive Angular Margin Loss for Deep Face Recognition","version":4},"cited_work":{"arxiv_id":"1801.07698","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1801.07698","snapshot_observed_at":"2026-07-02T07:06:44.682239Z","title":"Arcface: Additive angular margin loss for deep face recognition","venue":null,"work_id":"9943b136-0d32-4b32-816e-29f1fbc71604","year":2022},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"cited_paper":"/paper/1801.07698","citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:425e062a475fb47186ea278c0958ca2639e8e62e2a3f477ead4fd089bcb51a4c","observation_id":"3e151a70-6e72-421f-880a-133eaf249057","resolution":{"observed_at":"2026-05-25T17:21:05.135386Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dietterich","venue":null,"work_id":"fd044d7a-ad9e-40c8-b227-bd65bd54d37b","year":2000},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:d51d576559bd31b607449950246a5bef7f8b02097bda4290524cf28a8e97a038","observation_id":"c0c9bfa7-e8ef-4732-80fa-ac1b46f2abed","resolution":{"observed_at":"2026-05-25T17:21:06.079130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"[Gong et al., 2016] Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, and Bernhard Sch¨olkopf","venue":null,"work_id":"30b78fc5-2ecf-4afa-80a8-000dd0db28cf","year":2016},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:3c9dba9b7205e60858617f7e047030ac2c2b6d6e489c154a3fb32327a5469a50","observation_id":"b1a85f35-4ba6-4f0f-8bbf-b39720488e72","resolution":{"observed_at":"2026-05-25T17:21:06.119095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A kernel two-sample test","venue":null,"work_id":"97ee079d-fc06-4812-9033-6b49150b4b1c","year":2012},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:fd2a390789ec1ed3db73657c3370e22723807de81285eebcca0a85ae20835127","observation_id":"78edf9b9-8ed7-4676-ad0c-fb8c4297c77e","resolution":{"observed_at":"2026-05-25T17:21:06.122464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural network ensembles","venue":null,"work_id":"c94c9522-cf72-404d-a4f7-96b49b4c06c4","year":1990},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:ea124b95974debfca1f9d3cf6fc170da77bf55ed9e311b8df0163329f0fa90e1","observation_id":"6baf0311-ea46-43fe-a690-ed1d7b678b4b","resolution":{"observed_at":"2026-05-25T17:21:06.128158Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep residual learning for image recog- nition","venue":null,"work_id":"2df1bdb6-4f27-4aaa-ac04-2ec6203523c4","year":2016},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:d71783081a64a36ce35c520c60dfd7d178a3e169f21aaac1c525549f13750365","observation_id":"5cfd01df-90e3-410e-bf3f-7fc1d404d8e0","resolution":{"observed_at":"2026-05-25T17:21:06.138907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1503.02531","last_updated":"2015-03-09T15:44:49Z","snapshot_observed_at":"2026-07-06T04:11:24.157003Z","submitted_at":"2015-03-09T15:44:49Z","title":"Distilling the Knowledge in a Neural Network","version":1},"cited_work":{"arxiv_id":"1503.02531","doi":"10.1109/cvpr52733.2024.01515","metadata_source":"pith","pith_arxiv_id":"1503.02531","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Distilling the Knowledge in a Neural Network","venue":"stat.ML","work_id":"d927ab1f-17b8-4002-9d09-c3d55764fbad","year":2015},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"cited_paper":"/paper/1503.02531","citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:7dfa54080e3c3dea60c1ddc566cbd4e7bcb1ccefe585f6810e6ab51132286e7d","observation_id":"680a3d09-8ac5-4d1b-9fe9-8d92b8f3c454","resolution":{"observed_at":"2026-05-25T17:21:05.123223Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller","venue":null,"work_id":"2023ef64-4b13-4e92-bc56-48e3124185f5","year":2008},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:055e4324183cfeec71ba54f48fbaa748896cf08c809d4834318eb799ef0e57a7","observation_id":"b57e3e8f-f5f4-4024-89f8-2181405bcfe7","resolution":{"observed_at":"2026-05-25T17:21:06.112217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Weinberger","venue":null,"work_id":"59445712-e023-4ced-ab85-407f60843014","year":2016},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:ecbac56b9f74c49a08ef13cb180237de3dd1b80aef1ad99c05eaa6d763f8c1ac","observation_id":"adec52f9-a280-40ea-a846-2fc596c33f11","resolution":{"observed_at":"2026-05-25T17:21:06.115868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":"1412.6980","doi":"10.1002/mrm.28086","metadata_source":"pith","pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adam: A Method for Stochastic Optimization","venue":"cs.LG","work_id":"1910796d-9b52-4683-bf5c-de9632c1028b","year":2014},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:0501fa851f1bfc9cd98ad77c6dc2015f015bb9427832f550bf450df43c4db5b2","observation_id":"3888203b-6f7d-40f7-b870-9f5d74f62f96","resolution":{"observed_at":"2026-05-25T17:21:05.128710Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Agedb: The ﬁrst manually collected, in-the-wild age database","venue":null,"work_id":"8c910237-2f78-44f7-8475-7200a0a76d27","year":2017},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:29a27d5c8eb76a43bc0b80ab821d9f6acd65e8e02e73015deb7022efd0dd8951","observation_id":"47a8c4c1-8a27-407d-bc9a-ba9b8118fee6","resolution":{"observed_at":"2026-05-25T17:21:06.108459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Fitnets: Hints for thin deep nets","venue":null,"work_id":"b6a91667-653d-4ebb-9ce8-550f2d17851e","year":2015},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:b0eb385f38599da0e5f0b70ce79da1d5dbdfaa63836438971c3abd60b0e7243a","observation_id":"18961ab6-e38c-4170-91de-c2a58666a8d4","resolution":{"observed_at":"2026-05-25T17:21:06.104464Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Chen, Carlos Castillo, Vishal M","venue":null,"work_id":"4fe62148-cd18-4069-ae50-b3b26c6487e2","year":2016},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:62724a448387b0d8ba689e135627906feefefaabaf723fbee73ace2fb1f6fc17","observation_id":"90aed3de-36cc-44f9-8dd3-8c8745b4eb7c","resolution":{"observed_at":"2026-05-25T17:21:06.100537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Amalgamating knowledge towards comprehensive classiﬁcation","venue":null,"work_id":"f5040610-1a00-4799-906c-8490fb38cc20","year":2019},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:eb5e11703a5bbd5ddeee1932b0ecd693b568792012c395938925e3eb553b4c6a","observation_id":"095b140c-b35d-4526-8ebd-d18c733f2f9b","resolution":{"observed_at":"2026-05-25T17:21:06.142761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Swapout: Learning an ensemble of deep archi- tectures","venue":null,"work_id":"5fa08841-3495-49ef-8318-e8cc9d67a89b","year":2016},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:374e91880ccde623b8304fc51a68bd0c61f48b426390170f396c235be66d7b76","observation_id":"9650bc6a-d970-4f6c-8496-1bc9fc2bf2bf","resolution":{"observed_at":"2026-05-25T17:21:06.160722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hin- ton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov","venue":null,"work_id":"9c8306e3-061c-49ed-900c-e9a1a74cf231","year":2014},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:3e0f4784d1702ccf38db7bef979a1c08c84f5ee597d13dad4cee91df798b4ba3","observation_id":"8d56a703-c56b-4818-ac8f-1cc32d13d537","resolution":{"observed_at":"2026-05-25T17:21:06.156766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Going deeper with convolutions","venue":null,"work_id":"970e27ed-146f-4b05-8de8-7b809f988db0","year":2015},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:142848a684beffc0f0fba3c9000df6d6c23dfad91c2c57e3bb1e6d3a8167c4c9","observation_id":"e7022467-b0c4-4f14-8148-6e1ccdd7951c","resolution":{"observed_at":"2026-05-25T17:21:06.096470Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Regularization of neu- ral networks using dropconnect","venue":null,"work_id":"76bbaa07-dfec-470e-a5b3-47777a864ee9","year":2013},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:4e2a0650752194c7a677429cb45c5ae8e2b4cf51741b12c3cb3741a6e684fe4c","observation_id":"52d76d28-ad46-41c5-8584-ff0f94cb897f","resolution":{"observed_at":"2026-05-25T17:21:06.165606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Subspaces indexing model on Grassmann manifold for image search","venue":null,"work_id":"c2a19251-d4de-4e61-9a06-9bc4c422b13c","year":2011},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:943a1a7c5f9d482021023f3a3ed3a8f5544da9a84cbecfc5cdc067bc069ca0a1","observation_id":"8f3385cb-4ef2-481e-9771-501b5f4e20a9","resolution":{"observed_at":"2026-05-25T17:21:06.132390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Progressive blockwise knowledge distillation for neural network acceleration","venue":null,"work_id":"199c0cd1-1fb0-4650-8538-e1813d0ebcc1","year":2018},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:65b803d8dfeb867e9c0e5ea5b2baf4d41a9ef9c188374953aa5422ef1e18122c","observation_id":"2e5e4243-062a-47a1-9ef8-48091b04339b","resolution":{"observed_at":"2026-05-25T17:21:06.092550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Student becoming the master: Knowledge amalgamation for joint scene parsing, depth estimation, and more","venue":null,"work_id":"7084ac75-c97b-4a85-901f-86d053eb9fbb","year":2019},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:d307368ed6c12ebfc6652b16550a878f5802f79ab568fa57b36c90ef0071d8a5","observation_id":"95c1d94f-45b8-4662-8e66-51972e5b5389","resolution":{"observed_at":"2026-05-25T17:21:06.146755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1411.7923","last_updated":"2014-11-28T16:05:18Z","snapshot_observed_at":"2026-07-06T04:02:01.303133Z","submitted_at":"2014-11-28T16:05:18Z","title":"Learning Face Representation from Scratch","version":1},"cited_work":{"arxiv_id":"1411.7923","doi":null,"metadata_source":"pith","pith_arxiv_id":"1411.7923","snapshot_observed_at":"2026-07-10T15:47:23.413260Z","title":"Learning Face Representation from Scratch","venue":"cs.CV","work_id":"99fc2a3c-dec4-40dc-95f0-c258a721d5b0","year":2014},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"cited_paper":"/paper/1411.7923","citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:5f27e8e186fdb96026b72dd6a40c3069a1bb5a149c0528e4b8d8f1cac2e9bd0a","observation_id":"4a3f24c1-db25-4dba-bf2d-68c00f926ee2","resolution":{"observed_at":"2026-05-25T17:21:05.117560Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"On compressing deep models by low rank and sparse decomposition","venue":null,"work_id":"b1d57a83-f5e2-4569-8e2c-eb7f21d93a97","year":2017},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:5f9cbe3736ad7835ac06cc278dc059ed175941b269c30b95f5021f343ea00826","observation_id":"79891019-9293-44d1-a637-49a5975f3ecd","resolution":{"observed_at":"2026-05-25T17:21:06.150742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Taskonomy: Disentangling task transfer learn- ing","venue":null,"work_id":"4f151db5-7eb7-4381-97d3-abe3cbf1c013","year":2018},"citing_paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-25T17:17:45.029352Z"},"links":{"citing_paper":"/paper/1906.10546"},"observation_digest":"sha256:f4f3fab568feb13b9761464c5d0e771382bdbeb15d2b41f8495add232ae61f09","observation_id":"0d66c189-6f5f-43ae-8d8a-7ea086db978c","resolution":{"observed_at":"2026-05-25T17:21:06.087489Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1906.10546","last_updated":"2019-06-24T12:33:24Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2019-06-24T12:33:24Z","title":"Knowledge Amalgamation from Heterogeneous Networks by Common Feature Learning"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":4,"verified_fuzzy":21},"total_outbound_references":25},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:1906.10546."}