{"as_of":"2026-08-08T03:40:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:4c346cf072602bf365a6b1ae087fe19b563b12da4b0413ad4ca0b78af2977927","coverage":[{"denominator":16,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:29:06.514830Z","state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.18074/citation-record","integrity":"/paper/2506.18074/integrity","json":"/paper/2506.18074/citation-record.json","paper":"/paper/2506.18074"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:11.095824Z","title":"Evolutionary principles in self-referential learning, or on learning how to learn: the meta-meta-... hook,","venue":null,"work_id":"2720e933-025c-440c-a60d-f383a51ab7da","year":1987},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:04.424821Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:e447b0481bc5dc7e323c6d29e5bd07b5f9b5022f3a214865a50669276b6be45f","observation_id":"6ae81579-707f-4c77-bd1f-730abdf1a84f","resolution":{"observed_at":"2026-08-06T23:29:11.265560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:10.928963Z","title":"Meta- learning in neural networks: A survey,","venue":null,"work_id":"a28f192b-7382-4985-ae61-04dffc66e9cd","year":2021},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:04.554751Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:e08e096fcda302ac900e49ee80070d1045a3741fade437b4b11b98eedd4d18f3","observation_id":"5d122814-7494-4c82-8d3d-d5cb657664e9","resolution":{"observed_at":"2026-08-06T23:29:10.980089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:10.690345Z","title":"Meta-learning of neural state-space models using data from similar systems,","venue":null,"work_id":"5740d3f7-f93e-462c-9b00-2f7a122e01d1","year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:04.672058Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:b9e495ef954868d5c796b73d7b8d69b09a1dfbbbab2b575778feb58fb63a3587","observation_id":"dd1b9e7d-5356-4e88-85d9-62e114963fa6","resolution":{"observed_at":"2026-08-06T23:29:10.828221Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:10.511029Z","title":"From system models to class models: An in-context learning paradigm,","venue":null,"work_id":"2cfdbfa0-a4b4-4caa-91b8-4ce0a7a355bb","year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:04.774745Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:3fefdb72b3494af21f96d4bdea53a2f074211e683113749932f13806a6c6aec4","observation_id":"aa469839-bc0f-43c6-bfad-5c31ad72914a","resolution":{"observed_at":"2026-08-06T23:29:10.573665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:10.160842Z","title":"Adversarially robust few-shot learn- ing: A meta-learning approach,","venue":null,"work_id":"c82f6c18-7d9d-4b03-83c7-9176db21d2d0","year":2020},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:04.904738Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:d5715bf94f6e39331afe187ed73e45eafd9adf4a37c35970f808cc77037aec12","observation_id":"624a086d-9169-41b6-9964-0d51d9d8c1ec","resolution":{"observed_at":"2026-08-06T23:29:10.344842Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:09.814946Z","title":"Task-robust model- agnostic meta-learning,","venue":null,"work_id":"06abbd90-0600-4c13-a809-47278ae5d72c","year":2020},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.017372Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:f4900037ced3decd5e5f817b8a77e32403bd9f4be291e752a8e89cee430b02ef","observation_id":"50bdd4dd-1fe3-4ee6-8af5-e8d98b8a99e4","resolution":{"observed_at":"2026-08-06T23:29:09.944752Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:09.505788Z","title":"A simple yet effective strategy to robustify the meta learning paradigm,","venue":null,"work_id":"785ee30e-9a80-480d-b452-8eb7162aae1a","year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.204806Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:14203cfdc8203dc9450003a587347d51aeb1bea1729adc0f7135607680c3a158","observation_id":"b70eb544-7242-4f64-97a2-8fe984c58c9f","resolution":{"observed_at":"2026-08-06T23:29:09.624753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:09.214838Z","title":"Optimization of conditional value- at-risk,","venue":null,"work_id":"ff32fbd1-5acf-4e06-bdc0-76d0236f7cdf","year":2000},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.372892Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:e217e78c8942edb4469b3cd07e985315af51d3f4c824447d5f9408e92f31c55a","observation_id":"aa566c0c-276f-46b9-85a9-2f712e85f427","resolution":{"observed_at":"2026-08-06T23:29:09.314949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:08.929877Z","title":"Active learning for regression by inverse distance weighting,","venue":null,"work_id":"82dacea8-26c1-497d-81b1-b071751604d7","year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.554749Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:7207d10aec1aceaae300a5f4c43429eb5ecc1a8b51d66820c278e680d177e0dd","observation_id":"6d8f3942-0047-48a8-bd7e-a9f716e728d0","resolution":{"observed_at":"2026-08-06T23:29:09.054457Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:08.671872Z","title":"Frameworks and results in distribution- ally robust optimization,","venue":null,"work_id":"0bda7230-dd32-4ba7-9f9b-74649d2b004b","year":2022},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.764824Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:9232df66516f3d54327067f9a3375217659416115a97246e4c610732ed683e2a","observation_id":"5362a799-637d-4d80-a9ca-e907f178ac3e","resolution":{"observed_at":"2026-08-06T23:29:08.835916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.03291","last_updated":"2024-10-04T10:05:15Z","snapshot_observed_at":"2026-07-06T19:27:33.934338Z","submitted_at":"2024-10-04T10:05:15Z","title":"Enhanced Transformer architecture for in-context learning of dynamical systems","version":1},"cited_work":{"arxiv_id":"2410.03291","doi":null,"metadata_source":"pith","pith_arxiv_id":"2410.03291","snapshot_observed_at":"2026-08-06T23:29:07.174754Z","title":"Enhanced Transformer architecture for in-context learning of dynamical systems","venue":"cs.LG","work_id":"5edd5b39-736a-447f-b743-55b0006ccce9","year":2024},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:05.864848Z"},"links":{"cited_paper":"/paper/2410.03291","citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:d8ceb6d10a2c8472079b4c378f71b6cd9683e0dfc46298706a3913d66092420a","observation_id":"2d19a94d-6230-446a-9c63-0832282e87e4","resolution":{"observed_at":"2026-08-06T23:29:07.285074Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T23:29:06.001171Z","title":"GPT-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:06.001171Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:c247f11be05ff46ddb765e62bd6e6a3b37ce8d58458133dbca35a5c5e6b53e91","observation_id":"a065eb88-f540-45dc-957d-09977733dfb0","resolution":{"observed_at":"2026-08-06T23:29:06.001171Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:08.449293Z","title":"LipsFormer: Introducing Lipschitz Continuity to Vision Transformers,","venue":null,"work_id":"b4e03d6c-9f02-4dcf-91a0-ec9a10b95429","year":2023},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:06.134822Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:99b1faf4c7160621c7c912a666da9d347b07942670be358fb486d043fba6ca60","observation_id":"b86184f0-d698-4620-8759-2e3dcd17957a","resolution":{"observed_at":"2026-08-06T23:29:08.556863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:07.934777Z","title":"How smooth is attention?","venue":null,"work_id":"1d8ed224-6470-4e38-bae1-7bb06a283f6c","year":2024},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:06.234829Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:7eb1afc6f9a08d3393b364493975ffeb761281259e24fd20ff97200c5154a508","observation_id":"b5ba9058-0441-4114-ba6f-053228cc1bb8","resolution":{"observed_at":"2026-08-06T23:29:08.274755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:29:07.554770Z","title":"Three free data sets for development and benchmarking in nonlinear system identification,","venue":null,"work_id":"7a434586-cece-4df5-815f-9f6929d49806","year":2013},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:06.354918Z"},"links":{"citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:2b97d43d8da0f0f6c2355940545eb4f23cc04b5659858fb47c2894c7f1c28139","observation_id":"c88fd6fc-faa5-46e8-87e4-79e63c91816e","resolution":{"observed_at":"2026-08-06T23:29:07.684833Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.04458","last_updated":"2024-01-09T13:38:35Z","snapshot_observed_at":"2026-07-06T14:28:25.630901Z","submitted_at":"2022-12-08T18:30:22Z","title":"General-Purpose In-Context Learning by Meta-Learning Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.04458","snapshot_observed_at":"2026-08-06T23:29:06.514830Z","title":"General- purpose in-context learning by meta-learning transformers,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T23:29:06.514830Z"},"links":{"cited_paper":"/paper/2212.04458","citing_paper":"/paper/2506.18074"},"observation_digest":"sha256:d057ee04353cc339ea19ab7d039ecc38106adb27c6af40d3fff6a40bcd7db93d","observation_id":"d311f207-c96c-4db0-bcd6-872853083b06","resolution":{"observed_at":"2026-08-06T23:29:06.514830Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.18074","last_updated":"2025-06-22T15:41:22Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T23:21:00.641522Z","submitted_at":"2025-06-22T15:41:22Z","title":"Distributionally robust minimization in meta-learning for system identification"},"reference_resolution":{"displayed":16,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":1,"verified_fuzzy":13},"total_outbound_references":16},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2506.18074."}