{"as_of":"2026-08-19T14:29:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f6d27ad45d2a1bc7dfeba46a214c181cbe5e1b65bea9be856ce1d54523689db1","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":63,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":63,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+00:00","state":"measured"},{"denominator":63,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:56:26.454798Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":351,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2212.04089","last_updated":"2023-03-31T15:27:01Z","snapshot_observed_at":"2026-08-13T03:27:01.609831Z","submitted_at":"2022-12-08T05:50:53Z","title":"Editing Models with Task Arithmetic","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-13T08:09:12.716163Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2212.04089"},"observation_digest":"sha256:33bce929d566f7829b8c0917ac3584a08fdedc0e61f8384bfa84ad1ea86300fe","observation_id":"f9ff5b4a-b3b0-4ca7-911d-4b180819afb4","resolution":{"observed_at":"2026-05-13T08:09:12.958340Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-12T19:32:10.151837Z","title":"Deep ensembles: A loss landscape perspective,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2411.10649","last_updated":"2024-11-16T01:13:04Z","snapshot_observed_at":"2026-08-19T14:18:26.235164Z","submitted_at":"2024-11-16T01:13:04Z","title":"Deep Loss Convexification for Learning Iterative Models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T19:32:10.151837Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2411.10649"},"observation_digest":"sha256:7a5f252f8711164ae4e8248522735ab22fed375772ef0e030057ba58467a2467","observation_id":"2ac440c7-7f62-4ab7-bf67-45782f0580e9","resolution":{"observed_at":"2026-08-12T19:32:10.151837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-12T17:41:13.376016Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2411.14478","last_updated":"2024-11-19T09:36:48Z","snapshot_observed_at":"2026-08-19T13:30:06.482635Z","submitted_at":"2024-11-19T09:36:48Z","title":"Why you don't overfit, and don't need Bayes if you only train for one epoch","version":1},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-12T17:41:13.376016Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2411.14478"},"observation_digest":"sha256:a2e54a6fab238e9a557ac3f279b00bf7c14a69f77e1607e93957d6cc7bb0d807","observation_id":"acb3714f-600e-4050-bde6-81eacb8901e7","resolution":{"observed_at":"2026-08-12T17:41:13.376016Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-12T14:52:36.253520Z","title":"Deep ensembles: A loss landscape per- spective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2411.14860","last_updated":"2024-11-22T11:18:20Z","snapshot_observed_at":"2026-08-17T12:58:17.006548Z","submitted_at":"2024-11-22T11:18:20Z","title":"Ex Uno Pluria: Insights on Ensembling in Low Precision Number Systems","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-12T14:52:36.253520Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2411.14860"},"observation_digest":"sha256:bd136c84080a1c2c42733929f3a3f4ce9bb9d4c7c4c953896beb185fe01b4e92","observation_id":"2f1d7f52-78b1-4120-9860-6806f61cd7c9","resolution":{"observed_at":"2026-08-12T14:52:36.253520Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-12T13:45:38.739038Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2411.15944","last_updated":"2024-11-24T18:14:44Z","snapshot_observed_at":"2026-08-12T22:42:24.699578Z","submitted_at":"2024-11-24T18:14:44Z","title":"Customer Lifetime Value Prediction with Uncertainty Estimation Using Monte Carlo Dropout","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T13:45:38.739038Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2411.15944"},"observation_digest":"sha256:52185afdcb1d62ae58f77ae4310aba9def750aa9ae66abddc736ac616c3ba681","observation_id":"547c63c4-d2f5-4162-b7d4-877fc6051214","resolution":{"observed_at":"2026-08-12T13:45:38.739038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-11T20:47:09.056870Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2412.05475","last_updated":"2025-01-05T01:45:34Z","snapshot_observed_at":"2026-08-17T06:38:46.656523Z","submitted_at":"2024-12-07T00:22:58Z","title":"AI-powered Digital Twin of the Ocean: Reliable Uncertainty Quantification for Real-time Wave Height Prediction with Deep Ensemble","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-11T20:47:09.056870Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2412.05475"},"observation_digest":"sha256:34fb0677979b31104e7bb15c7dc86dac85de31c535a733252e49340d195e2311","observation_id":"3795009c-91b8-405e-93d9-74bc2f753b1e","resolution":{"observed_at":"2026-08-11T20:47:09.056870Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-11T19:15:01.465113Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2412.07077","last_updated":"2024-12-10T00:40:31Z","snapshot_observed_at":"2026-08-14T11:37:34.318179Z","submitted_at":"2024-12-10T00:40:31Z","title":"Retaining and Enhancing Pre-trained Knowledge in Vision-Language Models with Prompt Ensembling","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T19:15:01.465113Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2412.07077"},"observation_digest":"sha256:96e76ec63724fc2643d7fa957ebe4107f8ab4296c893c66d6deea25a33de428c","observation_id":"8217c723-6701-4d76-984a-28957de6a37e","resolution":{"observed_at":"2026-08-11T19:15:01.465113Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-10T20:33:04.229637Z","title":"Deep Ensembles : A Loss Landscape Perspective","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2501.08188","last_updated":"2025-01-14T15:13:00Z","snapshot_observed_at":"2026-08-14T13:00:38.720252Z","submitted_at":"2025-01-14T15:13:00Z","title":"A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T20:33:04.229637Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2501.08188"},"observation_digest":"sha256:4453694372eb1656524f10eefddc85a34dc95c401cb39d99a7b947830b04915e","observation_id":"d4f9108c-99e0-4f3c-b6bb-ab7449e41af2","resolution":{"observed_at":"2026-08-10T20:33:04.229637Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-10T19:13:24.102613Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2501.10561","last_updated":"2025-08-25T19:20:17Z","snapshot_observed_at":"2026-08-11T05:38:25.364755Z","submitted_at":"2025-01-17T21:31:11Z","title":"Early Failure Detection in Autonomous Surgical Soft-Tissue Manipulation via Uncertainty Quantification","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T19:13:24.102613Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2501.10561"},"observation_digest":"sha256:e0ea0a3cf9023f5d83f475d4ec90cb2c8a9ae1e3894730638bd1a3123460f2c8","observation_id":"af0217b8-9ac3-4e31-99b8-e17abaf3d2a5","resolution":{"observed_at":"2026-08-10T19:13:24.102613Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-09T20:29:52.495313Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2502.00089","last_updated":"2025-01-31T18:07:21Z","snapshot_observed_at":"2026-08-09T20:21:06.208133Z","submitted_at":"2025-01-31T18:07:21Z","title":"Ensembles of Low-Rank Expert Adapters","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-09T20:29:52.495313Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2502.00089"},"observation_digest":"sha256:69e5398095b0664201d8ca6f001f73f3f6e298e2ef4d7810cd8e963a735c2a0b","observation_id":"7360fbcf-18d8-46a8-9b60-7ecb94eb1e0f","resolution":{"observed_at":"2026-08-09T20:29:52.495313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-09T16:55:31.053209Z","title":"Deep ensembles: A loss landscape perspective,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2502.01035","last_updated":"2025-02-24T20:40:55Z","snapshot_observed_at":"2026-08-15T01:27:18.546745Z","submitted_at":"2025-02-03T04:14:20Z","title":"UASTHN: Uncertainty-Aware Deep Homography Estimation for UAV Satellite-Thermal Geo-localization","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-09T16:55:31.053209Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2502.01035"},"observation_digest":"sha256:b3d331eb83e8c798f659f2159f69abe201a5f0dd6448030af1edf8fa83847edc","observation_id":"3b0ef962-353c-4f60-ba77-9b9f2d1668fe","resolution":{"observed_at":"2026-08-09T16:55:31.053209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-08T05:32:34.777240Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2502.08355","last_updated":"2025-02-12T12:30:49Z","snapshot_observed_at":"2026-08-16T17:21:08.954311Z","submitted_at":"2025-02-12T12:30:49Z","title":"Loss Landscape Analysis for Reliable Quantized ML Models for Scientific Sensing","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T05:32:34.777240Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2502.08355"},"observation_digest":"sha256:844160c767b1cb0c50b4679237bc437d46b6e1263ac623ac378742335edbbeca","observation_id":"2f64d21f-ebc5-48b6-acc8-a6b76331b8a2","resolution":{"observed_at":"2026-08-08T05:32:34.777240Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-16T11:56:26.454798Z","title":"arXiv 1912.02757 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2504.14307","last_updated":"2025-06-23T20:04:22Z","snapshot_observed_at":"2026-08-18T15:55:46.666050Z","submitted_at":"2025-04-19T14:08:56Z","title":"Learning from Stochastic Teacher Representations Using Student-Guided Knowledge Distillation","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-16T11:56:26.454798Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2504.14307"},"observation_digest":"sha256:2090f36288d8e324c13e33f8a8f4eae2f08640ded3e88141791ccb62b80a6099","observation_id":"635f33ac-0bf5-4e80-9df6-fa8552a1e172","resolution":{"observed_at":"2026-08-16T11:56:26.454798Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2504.19239","last_updated":"2026-04-22T10:28:55Z","snapshot_observed_at":"2026-08-15T05:13:11.995553Z","submitted_at":"2025-04-27T13:46:03Z","title":"The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-22T18:52:54.219481Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2504.19239"},"observation_digest":"sha256:ff67054d5b47a49d06ec6739bee23f6cda939566e832dcbc7d5c1d0b4695b969","observation_id":"849279e6-23bb-46c0-b943-4ee17848ae71","resolution":{"observed_at":"2026-05-22T18:55:03.250527Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-15T23:17:28.367694Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.05143","last_updated":"2025-06-10T03:15:22Z","snapshot_observed_at":"2026-08-17T16:34:18.863983Z","submitted_at":"2025-05-08T11:27:31Z","title":"Sparse Training from Random Initialization: Aligning Lottery Ticket Masks using Weight Symmetry","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-15T23:17:28.367694Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.05143"},"observation_digest":"sha256:a0c775ba4fbe3d34f13d92f0dd9e8e6a29984cdbf3cac7d0e00716cb6182c99a","observation_id":"6b7221ef-c268-4d1b-bd1c-cff1a09d73e8","resolution":{"observed_at":"2026-08-15T23:17:28.367694Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-15T21:00:36.379576Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2505.11412","last_updated":"2025-05-16T16:21:45Z","snapshot_observed_at":"2026-08-19T04:33:14.813429Z","submitted_at":"2025-05-16T16:21:45Z","title":"Uncertainty quantification with approximate variational learning for wearable photoplethysmography prediction tasks","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-15T21:00:36.379576Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.11412"},"observation_digest":"sha256:e081c9e37a5a82f47fb05f77f49bda58e4ee74828678d2bc660124ed44a81d64","observation_id":"e6bb8558-ca52-432f-9eb0-80b85c0fdacd","resolution":{"observed_at":"2026-08-15T21:00:36.379576Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-15T21:11:54.181210Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2505.13501","last_updated":"2025-05-16T02:03:04Z","snapshot_observed_at":"2026-08-17T23:35:22.940914Z","submitted_at":"2025-05-16T02:03:04Z","title":"SPIEDiff: robust learning of long-time macroscopic dynamics from short-time particle simulations with quantified epistemic uncertainty","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-15T21:11:54.181210Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.13501"},"observation_digest":"sha256:d5db470ab0730bcf61ebfe584fdc06455ef4a8547742c6c45ba3d88992ee064f","observation_id":"ab55122c-64ce-4a6a-9fc6-57d0a554e119","resolution":{"observed_at":"2026-08-15T21:11:54.181210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T15:36:30.621955Z","title":"arXiv preprint arXiv:1912.02757 (2019)","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.14572","last_updated":"2025-05-20T16:31:09Z","snapshot_observed_at":"2026-08-16T07:48:37.871965Z","submitted_at":"2025-05-20T16:31:09Z","title":"Automated Fetal Biometry Assessment with Deep Ensembles using Sparse-Sampling of 2D Intrapartum Ultrasound Images","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T15:36:30.621955Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.14572"},"observation_digest":"sha256:e87f45ee57b0df1a3bbc8fcd4b4b70b7a9bde2d6745b56488b0850e1863c0732","observation_id":"441716cf-2151-4685-a6b6-9933a8a788d0","resolution":{"observed_at":"2026-08-07T15:36:30.621955Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T15:08:48.343895Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2505.16148","last_updated":"2025-05-22T02:46:08Z","snapshot_observed_at":"2026-08-11T01:38:59.697696Z","submitted_at":"2025-05-22T02:46:08Z","title":"NAN: A Training-Free Solution to Coefficient Estimation in Model Merging","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-07T15:08:48.343895Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.16148"},"observation_digest":"sha256:098ee770e8b886585c24a5e69bbef48a7ecee99a3bed3363e8841d7bd5194545","observation_id":"c10780f4-52c4-481a-b710-b08327abbb3a","resolution":{"observed_at":"2026-08-07T15:08:48.343895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T14:44:13.632238Z","title":"Deep Ensembles: A Loss Landscape Perspective , 2020","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2505.17909","last_updated":"2025-05-23T13:53:21Z","snapshot_observed_at":"2026-08-17T19:18:33.391509Z","submitted_at":"2025-05-23T13:53:21Z","title":"NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-07T14:44:13.632238Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.17909"},"observation_digest":"sha256:d90967a556a2c549e9a8caac21029b866e3d28abf75894d13a7d0bd86a954951","observation_id":"a5ca5e0a-a4d4-4818-b051-271d96a6202d","resolution":{"observed_at":"2026-08-07T14:44:13.632238Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T12:59:09.018060Z","title":"Deep en- sembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2505.23027","last_updated":"2025-05-29T03:12:56Z","snapshot_observed_at":"2026-08-15T19:44:27.969364Z","submitted_at":"2025-05-29T03:12:56Z","title":"Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T12:59:09.018060Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2505.23027"},"observation_digest":"sha256:546b67895418c5a14a2a98f2073f83cc87c2ebb81c73ce3cbf1d4bcfcf36e90c","observation_id":"62f62517-646a-42d8-8c4b-04dbf953a21a","resolution":{"observed_at":"2026-08-07T12:59:09.018060Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T05:24:50.952221Z","title":"Deep ensembles: A loss landscape perspec- tive.arXiv preprint arXiv:1912.02757, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2506.07984","last_updated":"2025-06-09T17:53:31Z","snapshot_observed_at":"2026-08-10T14:01:44.357247Z","submitted_at":"2025-06-09T17:53:31Z","title":"CXR-LT 2024: A MICCAI challenge on long-tailed, multi-label, and zero-shot disease classification from chest X-ray","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T05:24:50.952221Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2506.07984"},"observation_digest":"sha256:9c43ca1a8bfb348b8cf59527169bbdfdf183e05ec5786e3aea9df44f11b74c93","observation_id":"fde0c10e-f5de-4a42-8961-229a547211bb","resolution":{"observed_at":"2026-08-07T05:24:50.952221Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-07T00:30:35.075133Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.13972","last_updated":"2025-07-03T17:45:38Z","snapshot_observed_at":"2026-08-16T22:50:40.168604Z","submitted_at":"2025-06-16T20:22:07Z","title":"Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:30:35.075133Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2506.13972"},"observation_digest":"sha256:ce54b2aa5eed49623a0a65edce8530564cfd67b02f99f6e4de7038066222b8fe","observation_id":"0cf1255b-44f2-4e4b-a0e2-83970c4f9ab6","resolution":{"observed_at":"2026-08-07T00:30:35.075133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-06T20:05:34.519244Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.03863","last_updated":"2025-07-05T02:25:12Z","snapshot_observed_at":"2026-08-17T18:26:53.083189Z","submitted_at":"2025-07-05T02:25:12Z","title":"Enhanced accuracy through ensembling of randomly initialized auto-regressive models for time-dependent PDEs","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:05:34.519244Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2507.03863"},"observation_digest":"sha256:66714b2692413bb03a0d5cfd4972ca231c980fe079227b8533c59d1f4861943b","observation_id":"49232dc7-0318-406e-a6d5-11414a6990d6","resolution":{"observed_at":"2026-08-06T20:05:34.519244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-06T15:58:00.605528Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.14652","last_updated":"2025-09-09T18:55:34Z","snapshot_observed_at":"2026-08-14T03:11:13.070686Z","submitted_at":"2025-07-19T14:57:54Z","title":"Accelerating Hamiltonian Monte Carlo for Bayesian Inference in Neural Networks and Neural Operators","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T15:58:00.605528Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2507.14652"},"observation_digest":"sha256:c5016c9de438d9a6ba4090b8c37547b97ef61af857861a8c877682f35e818de6","observation_id":"bae07758-fc9d-4d00-a3cf-32931d685c12","resolution":{"observed_at":"2026-08-06T15:58:00.605528Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-06T11:44:48.317845Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.22493","last_updated":"2025-07-30T09:00:39Z","snapshot_observed_at":"2026-08-14T00:42:03.380813Z","submitted_at":"2025-07-30T09:00:39Z","title":"LVM-GP: Uncertainty-Aware PDE Solver via coupling latent variable model and Gaussian process","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T11:44:48.317845Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2507.22493"},"observation_digest":"sha256:af62777ad2b61c67208a7cd3e8fcf6718e39f323162e796807bfb6796d3d7fa1","observation_id":"946022fc-54ce-413d-8b79-8ca975dae7d5","resolution":{"observed_at":"2026-08-06T11:44:48.317845Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-06T10:40:53.870244Z","title":"Deep Ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2507.23543","last_updated":"2025-08-08T13:31:57Z","snapshot_observed_at":"2026-08-16T11:57:36.756691Z","submitted_at":"2025-07-31T13:34:06Z","title":"ART: Adaptive Relation Tuning for Generalized Relation Prediction","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T10:40:53.870244Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2507.23543"},"observation_digest":"sha256:e22a7be09026adeb1624cfbaa035b8c0402b7412dfe2e3106d5e41c7a95d5c37","observation_id":"0e984262-de88-4d80-b691-f7cd603485f0","resolution":{"observed_at":"2026-08-06T10:40:53.870244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T11:28:40.678068Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2509.02792","last_updated":"2025-09-02T19:53:43Z","snapshot_observed_at":"2026-08-17T20:18:22.810835Z","submitted_at":"2025-09-02T19:53:43Z","title":"Structured Basis Function Networks: Loss-Centric Multi-Hypothesis Ensembles with Controllable Diversity","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-05T11:28:40.678068Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2509.02792"},"observation_digest":"sha256:e3bd9d4ff21fa7079377be41ad957d651cec558edc5a982e824c0aa649f09684","observation_id":"bafb494b-ca48-4dec-96c6-069d7883c20a","resolution":{"observed_at":"2026-08-05T11:28:40.678068Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-15T15:49:46.700633Z","title":"Deep ensembles: A loss landscape per- spective.arXiv preprint arXiv:1912.02757,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2509.22082","last_updated":"2026-07-05T17:28:28Z","snapshot_observed_at":"2026-08-17T14:24:49.423007Z","submitted_at":"2025-09-26T09:04:25Z","title":"Trajectory-Aware Information Matching for Multi-Step Gradient Inversion in Federated Learning","version":3},"reference_index":2012,"source":"pdf_text","source_observed_at":"2026-08-15T15:49:46.700633Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2509.22082"},"observation_digest":"sha256:1378ec4f34c026117620238eabe3a739d49ac0f94b40d6fb98dabb3ca26ccaa7","observation_id":"aa2a93e4-5636-46ef-ae4f-96e5503c0a48","resolution":{"observed_at":"2026-08-15T15:49:46.700633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-03T20:33:48.466572Z","title":"Deep ensembles: A loss landscape perspective.ArXiv, abs/1912.02757, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2511.19636","last_updated":"2026-07-06T06:25:19Z","snapshot_observed_at":"2026-08-19T13:26:31.039130Z","submitted_at":"2025-11-24T19:12:26Z","title":"Exploring the Rashomon Set for Concept-Based Models","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-03T20:33:48.466572Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2511.19636"},"observation_digest":"sha256:0e0015fea09bb49f276541c94b346ad07cc315f7f30db37d5c04db060ec61512","observation_id":"1591e577-4fab-4aed-bcba-88f4e02df218","resolution":{"observed_at":"2026-08-03T20:33:48.466572Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2603.03190","last_updated":"2026-05-18T03:37:10Z","snapshot_observed_at":"2026-08-16T21:10:44.799529Z","submitted_at":"2026-03-03T17:47:09Z","title":"Expectation and Acoustic Neural Network Representations Enhance Music Identification from Brain Activity","version":3},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-21T11:36:06.967549Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2603.03190"},"observation_digest":"sha256:d3864f39ee611fa41d0a3e027b321e78d17f81372ed7e560f45e7cfc4f51df55","observation_id":"9a0685f0-527c-4ddf-91ca-62e07420a21d","resolution":{"observed_at":"2026-05-21T11:40:03.242209Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2604.04038","last_updated":"2026-08-17T04:11:03Z","snapshot_observed_at":"2026-08-19T11:17:08.668403Z","submitted_at":"2026-04-05T09:41:30Z","title":"FLAME: Condensing Ensemble Diversity into a Single Network for Efficient Sequential Recommendation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-13T17:29:06.884078Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2604.04038"},"observation_digest":"sha256:610afe0a83f340cb2712a96270d09d6fa147a557b9aa507940fd7c62c2636c2a","observation_id":"fe138a92-b651-4d54-8eab-56c334d54e61","resolution":{"observed_at":"2026-05-13T17:33:02.547560Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2604.07963","last_updated":"2026-04-09T08:25:03Z","snapshot_observed_at":"2026-07-06T22:57:09.435331Z","submitted_at":"2026-04-09T08:25:03Z","title":"Rethinking Data Mixing from the Perspective of Large Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T18:23:10.967220Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2604.07963"},"observation_digest":"sha256:0a83b7f0a46d2fd381b64494d5dfb59055672fecdf911b46acfafe13b6c7c2da","observation_id":"f7499393-2050-47bd-84a6-cc33d660643c","resolution":{"observed_at":"2026-05-11T00:41:05.883405Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2604.13992","last_updated":"2026-04-15T15:35:44Z","snapshot_observed_at":"2026-08-14T10:37:28.933265Z","submitted_at":"2026-04-15T15:35:44Z","title":"Physics-Informed Neural Networks for Methane Sorption: Cross-Gas Transfer Learning, Ensemble Collapse Under Physics Constraints, and Monte Carlo Dropout Uncertainty Quantification","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-10T14:04:32.279572Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2604.13992"},"observation_digest":"sha256:78b94f645950b5a16d09c3cb2b523b19e5d23ea9a5cf1a996cf393b789a297e3","observation_id":"8f8f5ce4-e471-4707-877c-b33c09d80de1","resolution":{"observed_at":"2026-05-10T14:05:29.150474Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2604.24708","last_updated":"2026-04-27T17:17:28Z","snapshot_observed_at":"2026-08-15T01:51:37.971821Z","submitted_at":"2026-04-27T17:17:28Z","title":"Scalable Hyperparameter-Divergent Ensemble Training with Automatic Learning Rate Exploration for Large Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T04:08:25.530778Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2604.24708"},"observation_digest":"sha256:0c53e511da85b25d7c39d4d1d19455daaf8a04a5d9d8e5635f813732f547c6c7","observation_id":"ac5e7557-7b9b-4f1c-905e-b8dd7ba53d18","resolution":{"observed_at":"2026-05-11T21:51:20.547192Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.07244","last_updated":"2026-05-08T05:01:40Z","snapshot_observed_at":"2026-08-15T21:47:26.504858Z","submitted_at":"2026-05-08T05:01:40Z","title":"Experience Sharing in Mutual Reinforcement Learning for Heterogeneous Language Models","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-11T02:02:41.411795Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.07244"},"observation_digest":"sha256:146fdf557b074f1005ab8682deb23d2974b482e387cc7ec381ac37c8092e99cd","observation_id":"7705e54b-00c7-4c5b-b5b6-66beb1943856","resolution":{"observed_at":"2026-05-11T04:00:55.087360Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.18472","last_updated":"2026-05-18T14:28:17Z","snapshot_observed_at":"2026-08-15T10:40:40.199687Z","submitted_at":"2026-05-18T14:28:17Z","title":"Flowing with Confidence","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-20T08:22:51.222059Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.18472"},"observation_digest":"sha256:2419cd6b024ee587195013bf3b752d5e92f227b9aa18316a2f140fba70687265","observation_id":"33db8a8a-6d39-47fe-ac1e-fd393bd07e41","resolution":{"observed_at":"2026-05-20T08:23:08.636545Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.20341","last_updated":"2026-06-06T13:10:56Z","snapshot_observed_at":"2026-08-14T01:57:01.718743Z","submitted_at":"2026-05-19T18:00:39Z","title":"Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-05-21T08:24:57.530663Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.20341"},"observation_digest":"sha256:8be87c1e0dc1b5e5ab85dbe21c024da9709be6d6148cae6a6f26e50a9c045114","observation_id":"c5f336b9-caf7-47f3-82f5-e996135714db","resolution":{"observed_at":"2026-05-21T08:29:53.119593Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.22390","last_updated":"2026-05-21T12:23:14Z","snapshot_observed_at":"2026-08-17T03:34:07.895037Z","submitted_at":"2026-05-21T12:23:14Z","title":"A Posterior-Predictive Variance Decomposition for Epistemic and Aleatoric Uncertainty in Wind Power Forecasting","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-22T07:44:59.345108Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.22390"},"observation_digest":"sha256:49432a1dfde9086bc80d02595226706fa53f747f4dfd59a30382c6c5a1f22dcc","observation_id":"f3452912-5c5f-4f08-83b6-881e631a30a4","resolution":{"observed_at":"2026-05-22T07:46:15.053524Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.22593","last_updated":"2026-05-21T15:07:47Z","snapshot_observed_at":"2026-08-18T13:25:03.336882Z","submitted_at":"2026-05-21T15:07:47Z","title":"Do Deep Ensembles Actually Capture Uncertainty in Graph Neural Networks?","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-22T07:08:16.449041Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.22593"},"observation_digest":"sha256:451cb33ca388c79a6de354c9bd709264bb0fd325ef5b40e0cee9bc2c2ab67fbe","observation_id":"e9d26d6d-cad4-4bd0-8790-cb443d187b63","resolution":{"observed_at":"2026-05-22T07:11:12.811334Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.23315","last_updated":"2026-05-22T07:32:07Z","snapshot_observed_at":"2026-08-18T17:25:08.622580Z","submitted_at":"2026-05-22T07:32:07Z","title":"Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-25T04:59:59.593160Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.23315"},"observation_digest":"sha256:6a9806fc23e6b0b07625c6ed045d21342aa156e5319a804fe6b159272cdb0bf2","observation_id":"1d0c996c-2ecd-434c-b836-5bf348793e51","resolution":{"observed_at":"2026-05-25T05:00:21.151018Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.24340","last_updated":"2026-05-23T01:52:50Z","snapshot_observed_at":"2026-08-15T15:58:55.603104Z","submitted_at":"2026-05-23T01:52:50Z","title":"ChainzRule: Sample-Efficient, Robust Deep Learning Across Tabular, NLP, and Vision Tasks","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-06-30T15:14:34.020391Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.24340"},"observation_digest":"sha256:8a617303d4ac9eb1a6d3d66f6827e7499f08ed68c1ed4b9841b4ac21cabefda2","observation_id":"eebe9cdf-b1a5-484d-b50b-02f5f8184962","resolution":{"observed_at":"2026-06-30T15:14:46.770746Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.27747","last_updated":"2026-05-26T22:44:58Z","snapshot_observed_at":"2026-08-14T15:16:04.313421Z","submitted_at":"2026-05-26T22:44:58Z","title":"Soft Specialists: $\\alpha$-R\\'enyi Ensembles for Uncertainty-Aware LLM Post-Training","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-29T15:14:28.128331Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.27747"},"observation_digest":"sha256:6296432125df3bb0de6f8ed0496745a8002e152b242c338adb08eb7ae655044d","observation_id":"a59a3d25-6aa2-4fa0-b581-be20e248fb46","resolution":{"observed_at":"2026-06-29T15:23:32.971694Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2605.30135","last_updated":"2026-05-28T16:02:49Z","snapshot_observed_at":"2026-08-14T15:34:03.699688Z","submitted_at":"2026-05-28T16:02:49Z","title":"DAMEL: Dual-Axis Multi-Expert Learning for Class-Imbalanced Learning","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-29T08:39:59.430880Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2605.30135"},"observation_digest":"sha256:4645bfd30cb28d8e9d17442848242635dab520ca4931ecaeb053e1fc0ac46b3e","observation_id":"27447cfa-63b2-45ef-b7d4-b15991a88960","resolution":{"observed_at":"2026-06-29T08:43:15.054598Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2606.03938","last_updated":"2026-06-03T02:07:12Z","snapshot_observed_at":"2026-08-03T04:36:58.198458Z","submitted_at":"2026-06-02T17:27:48Z","title":"q0: Primitives for Hyper-Epoch Pretraining","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T11:07:20.239027Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2606.03938"},"observation_digest":"sha256:80426a2bf516916a720103f9cbc2345b1ce2de5b90e5cbc37a9303d22ffaaf08","observation_id":"9f60fd2c-3402-47c3-a733-a2c449d7590e","resolution":{"observed_at":"2026-07-02T02:16:26.588106Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2606.10929","last_updated":"2026-06-09T14:38:26Z","snapshot_observed_at":"2026-07-06T23:50:06.645076Z","submitted_at":"2026-06-09T14:38:26Z","title":"Recoverable but Not Stationary:Local Linear Structures in Weights and Activations","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-06-27T13:51:39.893972Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2606.10929"},"observation_digest":"sha256:06bb89463e2c288efdaea653c18dffc799c8a00a172e0b159861b0fb4b0cf9ea","observation_id":"11a24d47-9570-4d5e-afc6-989e127fc4ba","resolution":{"observed_at":"2026-07-03T04:27:37.348400Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2606.20536","last_updated":"2026-06-18T17:49:32Z","snapshot_observed_at":"2026-08-14T16:22:44.635886Z","submitted_at":"2026-06-18T17:49:32Z","title":"The FID Lottery: Quantifying Hidden Randomness in Generative-Model Evaluation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-06-26T17:42:21.628047Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2606.20536"},"observation_digest":"sha256:93c847840a3e9b7409336c7212364eb740e242fb8710d6d523f04582e34f6a6d","observation_id":"4ebe8da0-c827-4faa-aa34-bf55fc3fb08c","resolution":{"observed_at":"2026-07-04T03:49:29.508159Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-07-11T10:00:17.827281Z","title":null,"venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.05019","last_updated":"2026-07-07T07:13:34Z","snapshot_observed_at":"2026-08-14T11:37:30.214233Z","submitted_at":"2026-07-06T12:59:45Z","title":"Beyond Modality Fusion: Deep Ensembles for Multimodal Classification","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-11T10:00:17.827281Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.05019"},"observation_digest":"sha256:b616a6eeae4ff7779ce16aab1925f593fb6d7c472ba6273dd33f9a65512dfa2c","observation_id":"4af57d2d-cf0a-47dc-9e82-36f5e02bce6b","resolution":{"observed_at":"2026-07-11T10:00:17.827281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2607.05380","last_updated":"2026-07-06T17:55:55Z","snapshot_observed_at":"2026-08-15T20:17:27.385865Z","submitted_at":"2026-07-06T17:55:55Z","title":"TabPack: Efficient Hyperparameter Ensembles for Tabular Deep Learning","version":1},"reference_index":136,"source":"arxiv_source","source_observed_at":"2026-07-07T13:54:51.466603Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.05380"},"observation_digest":"sha256:54023d3487f4a9d9d172c7ea47e285693e32c20635be76da0e93b0abc062bbec","observation_id":"86bd2ff4-7461-4401-9d45-61e65f63e851","resolution":{"observed_at":"2026-07-07T14:03:48.736431Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2607.06628","last_updated":"2026-07-07T12:12:43Z","snapshot_observed_at":"2026-08-17T16:49:09.314168Z","submitted_at":"2026-07-07T12:12:43Z","title":"Cross-Trajectory Chimera Interventions Reveal Dissociable Roles of Weight Magnitude and Direction in Grokking","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-11T01:08:44.982882Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.06628"},"observation_digest":"sha256:c10a9433fd3b19f021ae132f7606fbf6f09c6613d51e71104a9de6cfa17b9876","observation_id":"1d80db88-90ed-4715-ae00-ebe4a3aef3a4","resolution":{"observed_at":"2026-07-11T01:17:45.505491Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2607.06776","last_updated":"2026-07-07T20:17:05Z","snapshot_observed_at":"2026-08-18T19:17:49.613499Z","submitted_at":"2026-07-07T20:17:05Z","title":"Efficient Bayesian Deep Ensembles via Analytic Predictive Inference","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-10T21:34:38.656196Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.06776"},"observation_digest":"sha256:37d8746cce23830b5f79b2e262bae97abf15529e6afe4073f80bde8a093eab9d","observation_id":"ae2d4724-e143-455b-bf83-ee07f3130d52","resolution":{"observed_at":"2026-07-10T21:37:42.004110Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":"1912.02757","doi":"10.48550/arxiv.1912.02757","metadata_source":"pith","pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757","venue":"stat.ML","work_id":"73aa2dcc-7f2c-44a0-bad0-f5665b5fbad6","year":2019},"citing_paper":{"arxiv_id":"2607.08493","last_updated":"2026-07-09T13:53:02Z","snapshot_observed_at":"2026-08-13T17:07:15.753047Z","submitted_at":"2026-07-09T13:53:02Z","title":"Ensemble Diversity Optimization for Subjective Supervision","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-07-10T06:34:44.781898Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.08493"},"observation_digest":"sha256:56c982260aa618d44927efb6fbbebbdca9a89b7a92b2de2f680713338fe1896f","observation_id":"8b4fca59-ebd8-4286-ba97-062aa212d2cc","resolution":{"observed_at":"2026-07-10T06:36:52.472892Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-07-14T12:06:22.561885Z","title":null,"venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.10391","last_updated":"2026-07-11T16:44:25Z","snapshot_observed_at":"2026-08-14T16:50:43.760678Z","submitted_at":"2026-07-11T16:44:25Z","title":"Vertical Fusion: Condensing Internal Representations for Robust ViT Classification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-14T12:06:22.561885Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.10391"},"observation_digest":"sha256:2c60d9d7b8b589de7db0f404534c7b8aeb580ef76c4f5bcf93cde30b79a8e879","observation_id":"8527b905-7922-492f-b9e8-a0c1e2e1645c","resolution":{"observed_at":"2026-07-14T12:06:22.561885Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-07-14T04:52:20.985671Z","title":"Deep ensembles: A loss landscape perspective,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.11542","last_updated":"2026-07-13T13:28:31Z","snapshot_observed_at":"2026-08-19T12:25:00.096431Z","submitted_at":"2026-07-13T13:28:31Z","title":"Condition-Stratified Robustness Analysis of Post-Hoc Calibration Methods for Probabilistic Classifiers","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-14T04:52:20.985671Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.11542"},"observation_digest":"sha256:772c11d1710f375a4274cccb54ce253c25630d517ca2488db6427a79f7f70846","observation_id":"0eb23339-4846-4a63-aced-295ff1932b12","resolution":{"observed_at":"2026-07-14T04:52:20.985671Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-02T07:53:44.247942Z","title":"arXiv preprint arXiv:1912.02757 (2020)","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.16279","last_updated":"2026-07-09T14:55:45Z","snapshot_observed_at":"2026-08-16T22:03:49.257479Z","submitted_at":"2026-07-09T14:55:45Z","title":"A Step Forward Towards Trustworthy Risk-Aware Facial Retrieval (RA-FR)","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-02T07:53:44.247942Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.16279"},"observation_digest":"sha256:321c0c7e5fc0c19a42db7f0016018cc4e27146110edfc6adcccd00ee504c02fa","observation_id":"09c20fd9-1990-4904-b047-94badefd30b1","resolution":{"observed_at":"2026-08-02T07:53:44.247942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-01T19:55:49.217375Z","title":"Deep ensembles: A loss landscape perspective.arXiv preprint arXiv:1912.02757, 2019","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.16821","last_updated":"2026-07-18T13:43:44Z","snapshot_observed_at":"2026-08-07T16:44:16.045474Z","submitted_at":"2026-07-18T13:43:44Z","title":"First-Order Predictable but Pairwise Fragile: Local Task Adaptation in Trained Transformers","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-01T19:55:49.217375Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.16821"},"observation_digest":"sha256:9151e9167087d46d46a6560cf0b06e61f0d6ca436ae0a972a0fe142bb2a7f398","observation_id":"a208d961-81df-435a-a7ee-b4fd9b9d63b6","resolution":{"observed_at":"2026-08-01T19:55:49.217375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-02T09:18:45.469539Z","title":"Deep Ensembles: A Loss Landscape Perspective,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.18294","last_updated":"2026-06-30T21:45:41Z","snapshot_observed_at":"2026-08-07T04:04:23.180008Z","submitted_at":"2026-06-30T21:45:41Z","title":"Uncertainty Quantification for AI-Driven Crash Simulation Surrogates: A Comparative Study of Monte Carlo Dropout and Deep Ensemble on Open-Source Bumper Beam Benchmark","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-02T09:18:45.469539Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.18294"},"observation_digest":"sha256:623fc68d2799275c03e0bbb0c218a8945ba11fbb077163810541834581ad72bd","observation_id":"3ed1613b-8745-4b57-befb-6c541f13a9f6","resolution":{"observed_at":"2026-08-02T09:18:45.469539Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-01T15:25:09.428140Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.18484","last_updated":"2026-07-20T20:13:03Z","snapshot_observed_at":"2026-08-12T20:09:54.836094Z","submitted_at":"2026-07-20T20:13:03Z","title":"Search for new scalars via $X \\rightarrow SH \\rightarrow b\\bar{b}b\\bar{b}$ in proton-proton collisions at $\\sqrt{s} = 13$ TeV with the ATLAS detector","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-01T15:25:09.428140Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.18484"},"observation_digest":"sha256:6bace666539fec92fce5d5cb1a2b5a133a9db833380f5a44114ca0a70eb1c9ed","observation_id":"7f511372-101c-4e3b-89dc-c5b7aeed645c","resolution":{"observed_at":"2026-08-01T15:25:09.428140Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-01T05:59:04.483142Z","title":"Deep ensembles: A loss landscape perspective,","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.22068","last_updated":"2026-07-24T08:10:53Z","snapshot_observed_at":"2026-08-18T01:37:42.457116Z","submitted_at":"2026-07-24T08:10:53Z","title":"Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-01T05:59:04.483142Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.22068"},"observation_digest":"sha256:eb3450121c79da4f1e984f94eb01d0585bcea72686464d8039d89f94618237b7","observation_id":"93e117e7-9fff-4377-b667-baee1ddb69cc","resolution":{"observed_at":"2026-08-01T05:59:04.483142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-07-30T14:07:56.689567Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":1912},"citing_paper":{"arxiv_id":"2607.23860","last_updated":"2026-07-26T22:06:42Z","snapshot_observed_at":"2026-08-14T11:37:31.103404Z","submitted_at":"2026-07-26T22:06:42Z","title":"Controllable Diversity in Normalization-Based Implicit Ensembles via Softmax-Temperature Modulation","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-07-30T14:07:56.689567Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.23860"},"observation_digest":"sha256:aea85b3d29298c081bc6d4e72ce03aa0189a1283ae196b43cf06a70cf50cd085","observation_id":"e6e3e9e6-243e-4bce-b7ac-86596792d8b8","resolution":{"observed_at":"2026-07-30T14:07:56.689567Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-07-31T13:23:56.762521Z","title":"Farquhar, S., Kossen, J., Kuhn, L., Gal, Y ., 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.28248","last_updated":"2026-07-30T14:10:31Z","snapshot_observed_at":"2026-08-06T21:06:31.581639Z","submitted_at":"2026-07-30T14:10:31Z","title":"Uncertainty quantification for trustworthy deep learning: Methods and measures","version":1},"reference_index":1914,"source":"pdf_text","source_observed_at":"2026-07-31T13:23:56.762521Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2607.28248"},"observation_digest":"sha256:edbcb2d3b4162e2377524347b2bc9906d9e48e025857fd7354652b5cdc361e43","observation_id":"0f457107-9d67-4f3b-b4a7-bf21834bc871","resolution":{"observed_at":"2026-07-31T13:23:56.762521Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-05T00:38:51.189524Z","title":"Deep ensembles: A loss landscape perspective","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.00593","last_updated":"2026-08-01T11:12:39Z","snapshot_observed_at":"2026-08-14T22:23:16.417649Z","submitted_at":"2026-08-01T11:12:39Z","title":"Uncertainty-guided active learning for surrogate prediction of stream-finishing wear fields","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T00:38:51.189524Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2608.00593"},"observation_digest":"sha256:b6839092dac6002ac1d616ce304c10fa341e7cc33a68fbfadffad5c0fb36db6a","observation_id":"c7cc8097-465b-4035-88b7-a1fd8ba23983","resolution":{"observed_at":"2026-08-05T00:38:51.189524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1912.02757","snapshot_observed_at":"2026-08-15T16:23:16.644817Z","title":null,"venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.13123","last_updated":"2026-08-13T11:55:12Z","snapshot_observed_at":"2026-08-18T13:52:00.807594Z","submitted_at":"2026-08-13T11:55:12Z","title":"Using Diffusion Models to Estimate Uncertainties in Analytic Continuation","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-15T16:23:16.644817Z"},"links":{"cited_paper":"/paper/1912.02757","citing_paper":"/paper/2608.13123"},"observation_digest":"sha256:55fcd9c19d2856c9a649a4530ec345f6d25cf49588611a2c0d74207792028c3c","observation_id":"0b622313-ff38-424b-ad85-fb1172826940","resolution":{"observed_at":"2026-08-15T16:23:16.644817Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1912.02757/citation-record","integrity":"/paper/1912.02757/integrity","json":"/paper/1912.02757/citation-record.json","paper":"/paper/1912.02757"},"outbound":[],"paper":{"arxiv_id":"1912.02757","last_updated":"2020-06-25T03:57:04Z","latest_version":2,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-19T03:38:32.285921Z","submitted_at":"2019-12-05T17:48:18Z","title":"Deep Ensembles: A Loss Landscape Perspective"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 63 inbound Pith citation observations for arXiv:1912.02757."}