{"as_of":"2026-08-16T18:56:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f8e60ccc3185b2c76a311520664166786c72ec0351d6648e29a7d94cc956950e","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-12T13:40:10.137269Z","state":"measured"},{"denominator":50,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":50,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-10T01:23:58.565480Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-11T13:36:08.407242Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"cited_work":{"arxiv_id":"2411.16081","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.16081","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2411.16081 , year=","venue":null,"work_id":"50d8eb4e-3109-485e-91d9-da5b020079d8","year":null},"citing_paper":{"arxiv_id":"2604.20115","last_updated":"2026-04-22T02:27:24Z","snapshot_observed_at":"2026-08-06T07:07:13.291380Z","submitted_at":"2026-04-22T02:27:24Z","title":"On the Stability and Generalization of First-order Bilevel Minimax Optimization","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-05-10T01:23:58.565480Z"},"links":{"cited_paper":"/paper/2411.16081","citing_paper":"/paper/2604.20115"},"observation_digest":"sha256:7eb5689e27b7f37b1445d9b2df8ec99bb22c2bc72703ba4ba7cee7fb05ee844c","observation_id":"911f881c-7f83-4280-8387-e33a3a2b9bda","resolution":{"observed_at":"2026-05-11T13:36:08.413599Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2411.16081/citation-record","integrity":"/paper/2411.16081/integrity","json":"/paper/2411.16081/citation-record.json","paper":"/paper/2411.16081"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:40:10.749984Z","title":"Stability and generalization of bilevel programming in hyperpa- rameter optimization,","venue":null,"work_id":"eff4f6c3-4f24-455a-aad0-80e9418327ce","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.936504Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:d6b34d3b280a2315facf4773a8be1f16e22a14cdf345159cc767af91a491b044","observation_id":"810dde3c-1958-48a8-ac88-2c2ecc8363d3","resolution":{"observed_at":"2026-08-12T13:40:10.753692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.737826Z","title":"Gradient-based optimization of hyperparam- eters,","venue":null,"work_id":"c1d0f1db-21cc-4290-a161-8fbea403456c","year":1900},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.941256Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:f8a4deca6ee78fa5e7a63ad7cf5e98c6bb40af4ce2d9f20a33a6abad25791da1","observation_id":"4e2dd1f5-2d18-4b86-8276-9ec6caa965e7","resolution":{"observed_at":"2026-08-12T13:40:10.742766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.724491Z","title":"Forward and reverse gradient-based hyperparameter optimization,","venue":null,"work_id":"358fe67d-db6a-4820-a515-6ce0574ca369","year":2017},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.945414Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:6947f5ec3d53b00d8bf3c754e1b3d7b309fe6860d0d8734d7a27a2a2609016d2","observation_id":"30264943-f9e4-4f6c-a5d8-c02bf1c4ef35","resolution":{"observed_at":"2026-08-12T13:40:10.728963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.710385Z","title":"Bilevel programming for hyperparameter optimization and meta-learning,","venue":null,"work_id":"8f1a4d0d-db2c-46b1-a559-2c948b83a5e4","year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.949747Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:064315c10775b70697a5a9bb6c06ea52ca171c2eddcf5e2d686d429b1bb9fc61","observation_id":"ecf9987a-6fd1-40c3-8a28-93f0728bbc1e","resolution":{"observed_at":"2026-08-12T13:40:10.714500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.697365Z","title":"Optimizing millions of hyperparameters by implicit differentiation,","venue":null,"work_id":"34645258-8dc8-4537-8936-97be03b79930","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.954699Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:4518aff1a1365053ff603b15eba1a143383ff4421553ef63ec0c2a1558176a53","observation_id":"a657c160-aab2-4b40-8b0e-6659683a1e4e","resolution":{"observed_at":"2026-08-12T13:40:10.701440Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.680998Z","title":"On the iteration complexity of hypergradient computation,","venue":null,"work_id":"7fb7e3e5-834c-4452-af28-0b444e59f11e","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.958871Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:3f0ddedea3918ed8432ecc99ee784d2bc9ce11eed475c76f758b17993e09da82","observation_id":"5e4c1f7c-a879-4320-aae9-096d9a238781","resolution":{"observed_at":"2026-08-12T13:40:10.686171Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.667390Z","title":"Implicit differentiation of lasso-type models for hyperparameter optimization,","venue":null,"work_id":"cc3cc2d5-55c8-4933-af92-4cdd3c312737","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.963127Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:e94df3305552c0978235fcbd0262454a7b262e5c051d46f298043bf68903859b","observation_id":"7ca1a3a5-ca89-49d9-8bf6-1ff0b10efe9f","resolution":{"observed_at":"2026-08-12T13:40:10.671451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.08136","last_updated":"2019-07-24T14:43:31Z","snapshot_observed_at":"2026-08-14T19:12:55.572755Z","submitted_at":"2018-05-21T15:44:51Z","title":"Meta-learning with differentiable closed-form solvers","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.08136","snapshot_observed_at":"2026-08-12T13:40:09.967146Z","title":"Meta-learning with differentiable closed-form solvers,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.967146Z"},"links":{"cited_paper":"/paper/1805.08136","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:1567e62942375aa0b25fac8cebe46f06ad68436b42a79ae6898118d345c24565","observation_id":"e255f097-eb38-4b19-892e-19acbdd22198","resolution":{"observed_at":"2026-08-12T13:40:09.967146Z","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":"2026-08-12T13:40:10.656030Z","title":"Convergence of meta-learning with task-specific adaptation over partial parameters,","venue":null,"work_id":"05309b06-3660-4cf9-bd71-3d281456fb85","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.972997Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:584e6205fccc6050d16d789f1dc41cce3d15be7715eb800afc143b3cda1e9618","observation_id":"fd1e4d62-a83a-411b-9331-544bd75f81fb","resolution":{"observed_at":"2026-08-12T13:40:10.659829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:40:09.976496Z","title":"Model-agnostic meta-learning for fast adaptation of deep networks,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.976496Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:824cf5b698f0a80e66ecc88e4cbc5511cd0ecfea37ef5b3811a272810d9c55be","observation_id":"decec390-9073-41ac-858d-9fc4869aa832","resolution":{"observed_at":"2026-08-12T13:40:09.976496Z","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":"2026-08-12T13:40:10.633901Z","title":"Meta-learning with implicit gradients,","venue":null,"work_id":"dc62e537-1001-40e4-aaf7-94f837925230","year":2019},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.979872Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:5851843d1bf4c22b3cec9a0a5ee8e69d63e0447d8d22563d74b0a7f6850a121d","observation_id":"fce679c0-fb63-4768-8649-1c0c1b970207","resolution":{"observed_at":"2026-08-12T13:40:10.637385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.623219Z","title":"Autoaugment: Learning augmentation strate- gies from data,","venue":null,"work_id":"0b42498e-f20c-4ffc-b9ab-1a90bb166cbb","year":2019},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.983879Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:8f3c24f79d1c278f1f501471af688d7d94b3f654becdf5171910615431949794","observation_id":"994e5c15-1522-4697-b6da-4b1e857b3457","resolution":{"observed_at":"2026-08-12T13:40:10.627037Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.13695","last_updated":"2022-02-07T20:52:52Z","snapshot_observed_at":"2026-08-16T18:14:28.017154Z","submitted_at":"2021-06-25T15:28:48Z","title":"CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.13695","snapshot_observed_at":"2026-08-12T13:40:09.987466Z","title":"Cadda: Class-wise automatic differentiable data augmentation for eeg signals,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.987466Z"},"links":{"cited_paper":"/paper/2106.13695","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:05f212e26218b03b1208711c61e22401dad6397f44ff5eeef57c345c91d45f07","observation_id":"547c7943-9cdd-4976-b83d-b537e8ea6c84","resolution":{"observed_at":"2026-08-12T13:40:09.987466Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1806.09055","last_updated":"2019-04-23T06:29:32Z","snapshot_observed_at":"2026-08-15T06:40:14.261008Z","submitted_at":"2018-06-24T00:06:13Z","title":"DARTS: Differentiable Architecture Search","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1806.09055","snapshot_observed_at":"2026-08-12T13:40:09.991267Z","title":"Darts: Differentiable architecture search,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.991267Z"},"links":{"cited_paper":"/paper/1806.09055","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:132d1a861efba0cfa968e3cbef0c1bda067d5f21f25409bd8a0ec82de51b52e3","observation_id":"37b5f38b-99da-4b27-a793-fb9949752144","resolution":{"observed_at":"2026-08-12T13:40:09.991267Z","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":"2026-08-12T13:40:10.611529Z","title":"Deep bilevel learning,","venue":null,"work_id":"fe4dd5f9-569e-44b8-be77-989d47d52f5d","year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.995245Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:1dd6579f6f883b240bbc3dd0684e03a3cb778153599b750f882352f870846756","observation_id":"2a049a47-4f0a-4e61-b2b7-752722ecfb83","resolution":{"observed_at":"2026-08-12T13:40:10.615299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.600115Z","title":"Automatic design of cnns via differentiable neural architecture search for polsar image classification,","venue":null,"work_id":"166e3601-77db-4c19-8266-a79234f90072","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:09.998873Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:3242af3e2ae3252ad6c63e6d616d25bec732860ab24811ebec2ea8e4aea15164","observation_id":"f19ebfd0-57a2-4169-a553-8d11ae0c503f","resolution":{"observed_at":"2026-08-12T13:40:10.603775Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.583608Z","title":"Advancing model pruning via bi-level optimization,","venue":null,"work_id":"1e8471fe-13be-4fc0-a806-d24f538dc022","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.003517Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:96be335cabc3a652cb8b412a375215735f9f5457e215458541f6710ef995b618","observation_id":"1e72b47e-c42e-47f4-858c-f5a2261f694d","resolution":{"observed_at":"2026-08-12T13:40:10.588209Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.573353Z","title":"Anti-makeup: Learning a bi-level adversarial network for makeup- invariant face verification,","venue":null,"work_id":"d230857b-9b42-4674-bba4-562b71a15502","year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.007409Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:85973c99f6446758ebbf011f3b4f3636b404a5ee414ebca69979d528bf1175a2","observation_id":"07c744ff-f983-4b34-9d35-856c5f93b288","resolution":{"observed_at":"2026-08-12T13:40:10.576912Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1610.01945","last_updated":"2017-01-18T18:10:00Z","snapshot_observed_at":"2026-08-14T21:36:23.051831Z","submitted_at":"2016-10-06T17:00:54Z","title":"Connecting Generative Adversarial Networks and Actor-Critic Methods","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1610.01945","snapshot_observed_at":"2026-08-12T13:40:10.011546Z","title":"Connecting generative adver- sarial networks and actor-critic methods,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.011546Z"},"links":{"cited_paper":"/paper/1610.01945","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:332bee1269a018c480162cb11c367f36b2eea09d9f5efb2913d1bc7a46060fca","observation_id":"2c0ecfb0-962a-4de2-a9ba-6bc87779ebf6","resolution":{"observed_at":"2026-08-12T13:40:10.011546Z","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":"2026-08-12T13:40:10.562764Z","title":"On the global optimality of model-agnostic meta-learning,","venue":null,"work_id":"34928e21-bb97-48f5-823a-b5819c7ed519","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.016408Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:d80e502ef0de4ce40e3b7dd47527ee7d8de996f1b63e940ab7577a2a1d9e6a69","observation_id":"9c3c66f1-fae1-49a5-8947-32f50c7f5ce2","resolution":{"observed_at":"2026-08-12T13:40:10.566387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.551780Z","title":"A two- timescale stochastic algorithm framework for bilevel op- timization: Complexity analysis and application to actor- critic,","venue":null,"work_id":"c2476044-594f-4a1d-8d0b-8960b9944045","year":2023},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.020199Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:694b6286f053f6a4727b8a0ac4a72496774fc02098a197d8b655c7aff128067f","observation_id":"b97da8e9-1479-4d3d-8de8-0a91d9e604f2","resolution":{"observed_at":"2026-08-12T13:40:10.555662Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.541265Z","title":"Randomized stochastic variance- reduced methods for stochastic bilevel optimization,","venue":null,"work_id":"20bad060-32b9-4f7c-acf4-3985324556e1","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.023746Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:9eb914858aa1a6965fe1811affa1bd380e5f1771632c60305589c131c698a8e7","observation_id":"c7f56323-0ca7-4093-9518-eb5edc116808","resolution":{"observed_at":"2026-08-12T13:40:10.544892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1802.02246","last_updated":"2018-02-06T22:10:14Z","snapshot_observed_at":"2026-08-16T15:51:37.195604Z","submitted_at":"2018-02-06T22:10:14Z","title":"Approximation Methods for Bilevel Programming","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.02246","snapshot_observed_at":"2026-08-12T13:40:10.027526Z","title":"Approximation methods for bilevel programming,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.027526Z"},"links":{"cited_paper":"/paper/1802.02246","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:4e74577148694dbb6a347cd8af1af3143e5845fdc0476ed91f3f3851af2293fa","observation_id":"f06ff210-3656-4c22-bae3-97c08a6e66c4","resolution":{"observed_at":"2026-08-12T13:40:10.027526Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.05170","last_updated":"2022-06-08T05:49:52Z","snapshot_observed_at":"2026-08-14T16:12:50.514842Z","submitted_at":"2020-07-10T05:20:02Z","title":"A Two-Timescale Framework for Bilevel Optimization: Complexity Analysis and Application to Actor-Critic","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.05170","snapshot_observed_at":"2026-08-12T13:40:10.031504Z","title":"A two- timescale framework for bilevel optimization: Complex- ity analysis and application to actor-critic,","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.031504Z"},"links":{"cited_paper":"/paper/2007.05170","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:53416e35d24fba07c143b264e0c92d0f97c061150953bfbba568f8b9147e421f","observation_id":"14639e23-ba14-4230-bdbe-3ae5ccbcbe87","resolution":{"observed_at":"2026-08-12T13:40:10.031504Z","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":"2026-08-12T13:40:10.530321Z","title":"Closing the gap: Tighter analysis of alternating stochastic gradient methods for bilevel problems,","venue":null,"work_id":"b13e6b66-3a96-49b4-9538-9042d1095e86","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.035445Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:8affef2c44e53b5b6111f99721868abff41f2bca50200e764e759d4c0a2ea700","observation_id":"147dd726-75f9-4f0e-bb0b-659db2bd6092","resolution":{"observed_at":"2026-08-12T13:40:10.534256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.519242Z","title":"Provably faster algorithms for bilevel optimization,","venue":null,"work_id":"5e17cb19-e4a8-4ceb-aeea-4b61050cf6eb","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.039250Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:0d405084401d3bd5fb9a91cdd604173393007b05ab9f2f1685323c3d25181421","observation_id":"2212e8b9-aba6-4d25-a48b-833a2bc535ae","resolution":{"observed_at":"2026-08-12T13:40:10.523225Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04671","last_updated":"2022-03-31T02:39:25Z","snapshot_observed_at":"2026-08-16T18:46:51.217943Z","submitted_at":"2021-02-09T06:35:30Z","title":"A Single-Timescale Method for Stochastic Bilevel Optimization","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.04671","snapshot_observed_at":"2026-08-12T13:40:10.042586Z","title":"A single-timescale stochastic bilevel optimization method,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.042586Z"},"links":{"cited_paper":"/paper/2102.04671","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:7a427302399e71dda0d5e6799aac46a2d3d90ab9cf0aaa169476f5d68a9b5cd5","observation_id":"1541c1eb-d14d-48c8-bc55-3973d4a72141","resolution":{"observed_at":"2026-08-12T13:40:10.042586Z","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":"2026-08-12T13:40:10.508555Z","title":"Bilevel optimization: Con- vergence analysis and enhanced design,","venue":null,"work_id":"59f93c85-2274-4742-92f0-b044021d5064","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.046841Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:e39553c71670a85e79a95a34fb2cb71c8444bd065b83b67637484bdd2909e3da","observation_id":"72083d17-7db2-43ea-8596-7acf3df9f16c","resolution":{"observed_at":"2026-08-12T13:40:10.512164Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.496969Z","title":"A framework for bilevel optimization that enables stochas- tic and global variance reduction algorithms,","venue":null,"work_id":"d38de902-bb12-4ad7-9502-2668088bc68a","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.050380Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:4d84d7152bb4cf3f3f4ad4ece67119d9179e7005230ba3821045cf172d13c507","observation_id":"0e178f38-b1ae-4b92-894b-6e213398ffbd","resolution":{"observed_at":"2026-08-12T13:40:10.500873Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.14580","last_updated":"2022-07-11T14:05:08Z","snapshot_observed_at":"2026-08-16T17:38:37.437816Z","submitted_at":"2021-11-29T15:10:09Z","title":"Amortized Implicit Differentiation for Stochastic Bilevel Optimization","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.14580","snapshot_observed_at":"2026-08-12T13:40:10.053973Z","title":"Amortized implicit differenti- ation for stochastic bilevel optimization,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.053973Z"},"links":{"cited_paper":"/paper/2111.14580","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:9da246f12a40de8c2b56b70a7b30fa4e0711fbca05a27bbd87206ee301b3760a","observation_id":"f69c0baf-7359-4937-bc17-8beb69bfe1bb","resolution":{"observed_at":"2026-08-12T13:40:10.053973Z","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":"2026-08-12T13:40:10.486306Z","title":"Projection-free stochastic bi-level optimization,","venue":null,"work_id":"06467ac2-a6c0-4e3a-b12f-5bfc71e9b51b","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.057824Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:97dd663f1cff99d14c3bb7d531d7e0c14e8faf1b3616e91d19b57a655babd460","observation_id":"6cf6aad7-901a-4afc-aecb-e570bd24ae1e","resolution":{"observed_at":"2026-08-12T13:40:10.489959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.475080Z","title":"Fednest: Federated bilevel, minimax, and com- positional optimization,","venue":null,"work_id":"28e30f0e-af8a-48df-bbcb-284edae65aab","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.063319Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:9555d871eaba561c403ab282fd895dcf28d8e29886e0a395b83ed8821b61db06","observation_id":"56b0d415-b81a-45a1-b995-f97f43ac7c2a","resolution":{"observed_at":"2026-08-12T13:40:10.478701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.12839","last_updated":"2023-05-31T23:36:56Z","snapshot_observed_at":"2026-08-16T16:21:49.369494Z","submitted_at":"2022-10-23T20:06:05Z","title":"Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity","version":2},"cited_work":{"arxiv_id":"2210.12839","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.12839","snapshot_observed_at":"2026-08-12T13:40:10.280955Z","title":"Decentralized Stochastic Bilevel Optimization with Improved per-Iteration Complexity","venue":"math.OC","work_id":"e78f231a-5575-41c5-a083-961e63cff221","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.067022Z"},"links":{"cited_paper":"/paper/2210.12839","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:379dc2dd9060f122cca2853d147c5034431dbfb4cb0e9c149db188b000eefbf8","observation_id":"660b61c8-649f-40ce-9e70-84ca9cb17c9f","resolution":{"observed_at":"2026-08-12T13:40:10.285234Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.463098Z","title":"Stability and generaliza- tion,","venue":null,"work_id":"fd457d94-5e7c-4f2b-89bb-eafc059acd65","year":2002},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.071404Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:5ef7caf2102a2874e30e3542d6037b7fe1062cc2931a123416946227c4e4d837","observation_id":"f01ccef1-2ed5-421a-aa96-9b7cff8274a7","resolution":{"observed_at":"2026-08-12T13:40:10.467270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.452149Z","title":"Stability of randomized learning algorithms","venue":null,"work_id":"4ad6de95-87aa-4543-a227-f678a4cb89b6","year":2005},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.075088Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:edf599b2f4f64f3911e7829f7c968ca0e820896987b45be0f00c8c8a0d1af7e3","observation_id":"0a74c11a-bba5-4b09-94e0-a9c218ffcc3f","resolution":{"observed_at":"2026-08-12T13:40:10.455821Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.438636Z","title":"Train faster, gener- alize better: Stability of stochastic gradient descent,","venue":null,"work_id":"fdd7fd91-b3c0-4d6b-b1b7-249915549439","year":2016},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.078946Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:dce4c2ea95a616087d61f1651e552ee650e120a1a53abb3a6ecf273a818b2465","observation_id":"d8364512-c410-406f-84df-f5781bc500fb","resolution":{"observed_at":"2026-08-12T13:40:10.443138Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.01619","last_updated":"2018-04-04T22:23:40Z","snapshot_observed_at":"2026-08-14T19:29:11.470321Z","submitted_at":"2018-04-04T22:23:40Z","title":"Stability and Convergence Trade-off of Iterative Optimization Algorithms","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.01619","snapshot_observed_at":"2026-08-12T13:40:10.082493Z","title":"Stability and convergence trade-off of iterative optimization algorithms,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.082493Z"},"links":{"cited_paper":"/paper/1804.01619","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:8746a8420bae68d487c60d11e8d2165f11b25d92511415c3bae450c63206dc80","observation_id":"8e4e07dd-6805-4855-974f-2646c20fdf04","resolution":{"observed_at":"2026-08-12T13:40:10.082493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2206.04502","last_updated":"2022-06-20T14:35:33Z","snapshot_observed_at":"2026-08-16T16:54:10.410863Z","submitted_at":"2022-06-09T13:39:06Z","title":"What is a Good Metric to Study Generalization of Minimax Learners?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2206.04502","snapshot_observed_at":"2026-08-12T13:40:10.086554Z","title":"What is a good metric to study generalization of minimax learners?","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.086554Z"},"links":{"cited_paper":"/paper/2206.04502","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:7b0175e6fd4435140efae663745d2fd1df323ce95f5ef2827888a2a6424135d2","observation_id":"aea083f8-f7ad-4905-ae32-512995aea784","resolution":{"observed_at":"2026-08-12T13:40:10.086554Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.00960","last_updated":"2022-10-31T09:39:54Z","snapshot_observed_at":"2026-08-16T16:27:19.429705Z","submitted_at":"2022-10-03T14:21:46Z","title":"Stability Analysis and Generalization Bounds of Adversarial Training","version":2},"cited_work":{"arxiv_id":"2210.00960","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.00960","snapshot_observed_at":"2026-08-12T13:40:10.245271Z","title":"Stability Analysis and Generalization Bounds of Adversarial Training","venue":"cs.LG","work_id":"10970a8e-d283-4cad-9298-f9b87177c901","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.090668Z"},"links":{"cited_paper":"/paper/2210.00960","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:7d77438ba7632eb1a3160ad11a43f21a359e64c3b9eab106c59d9bcdc349893c","observation_id":"321acade-9880-420c-bfb5-b9c56202684a","resolution":{"observed_at":"2026-08-12T13:40:10.249068Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.20369","last_updated":"2023-10-31T11:27:01Z","snapshot_observed_at":"2026-08-16T14:47:16.235271Z","submitted_at":"2023-10-31T11:27:01Z","title":"Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm","version":1},"cited_work":{"arxiv_id":"2310.20369","doi":null,"metadata_source":"pith","pith_arxiv_id":"2310.20369","snapshot_observed_at":"2026-08-12T13:40:10.230333Z","title":"Stability and Generalization of the Decentralized Stochastic Gradient Descent Ascent Algorithm","venue":"cs.LG","work_id":"20af34f1-6565-412a-951e-972a79681e55","year":2023},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.094502Z"},"links":{"cited_paper":"/paper/2310.20369","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:18b9c881764f8f6a8725bf82518daf8e7c72f06e58273960f04bee79ba27142f","observation_id":"eee2fbc9-6eb1-4e33-bba0-4386b403ca96","resolution":{"observed_at":"2026-08-12T13:40:10.234512Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.425370Z","title":"Stability and generalization of decentralized stochastic gradient descent,","venue":null,"work_id":"a2003e96-5dff-4050-942a-12289199a3d7","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.099097Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:46e14077594f734edd673fc093081aa9bd3764774fe590ddbd056d69ca050595","observation_id":"50dc90e3-f606-419b-800d-d9df298d1bbc","resolution":{"observed_at":"2026-08-12T13:40:10.429199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.412661Z","title":"Topology-aware generalization of decentralized sgd,","venue":null,"work_id":"770c1ccf-bff5-47f5-abb3-125e8d1fc087","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.104214Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:c3e18fdb6a6a8260e77f3e1318c8743df8ce18e993fe6579cd04cb58384a3106","observation_id":"2e72b9cc-b3be-48ec-bd12-034a6edbe4a2","resolution":{"observed_at":"2026-08-12T13:40:10.416528Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.401027Z","title":"A closer look at the training strategy for modern meta-learning,","venue":null,"work_id":"0014968b-3470-4b5c-9af3-82479f5b190e","year":2020},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.108267Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:d3f7aee9efd6dce1d44fbc24710efd17e40a991a7db4d4a5a0a923c627c29684","observation_id":"de882bdb-84d6-43d3-8206-eef98f7cb6cf","resolution":{"observed_at":"2026-08-12T13:40:10.405294Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-12T13:40:10.389471Z","title":"Generalization of model-agnostic meta-learning algorithms: Recurring and unseen tasks,","venue":null,"work_id":"76a16bfb-801a-4626-a69e-83fceefd2d38","year":2021},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.114971Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:efca9765f506daf00c07c915b35b88cd17712e8d7da48329c386833248aa5df0","observation_id":"e5dbc439-2d3b-41e8-acb6-462fc9c66180","resolution":{"observed_at":"2026-08-12T13:40:10.393466Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.14224","last_updated":"2022-06-01T00:57:57Z","snapshot_observed_at":"2026-08-16T16:57:04.899616Z","submitted_at":"2022-05-27T20:28:52Z","title":"Will Bilevel Optimizers Benefit from Loops","version":3},"cited_work":{"arxiv_id":"2205.14224","doi":null,"metadata_source":"pith","pith_arxiv_id":"2205.14224","snapshot_observed_at":"2026-08-12T13:40:10.210297Z","title":"Will Bilevel Optimizers Benefit from Loops","venue":"cs.LG","work_id":"f0b2e9be-73bb-4af6-ab99-bb98b09e35ad","year":2022},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.119797Z"},"links":{"cited_paper":"/paper/2205.14224","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:ea54dcf5d21e8a03bd035b70e16cd0552cec7aaf707906b6e16e577d6e4a38b2","observation_id":"02d3c9c8-9d51-4040-b41c-4f8fb2758408","resolution":{"observed_at":"2026-08-12T13:40:10.217323Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.12067","last_updated":"2023-06-21T07:32:29Z","snapshot_observed_at":"2026-08-16T15:22:19.270200Z","submitted_at":"2023-06-21T07:32:29Z","title":"Optimal Algorithms for Stochastic Bilevel Optimization under Relaxed Smoothness Conditions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.12067","snapshot_observed_at":"2026-08-12T13:40:10.124082Z","title":"Opti- mal algorithms for stochastic bilevel optimization un- der relaxed smoothness conditions,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.124082Z"},"links":{"cited_paper":"/paper/2306.12067","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:843cd030150dc6c72fc9051299880e59e12cacfd578096ac9842c8159b0acf6d","observation_id":"dfb13727-e791-4f85-a574-1c71b4a221fb","resolution":{"observed_at":"2026-08-12T13:40:10.124082Z","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":"2026-08-12T13:40:10.377808Z","title":"The mnist database of handwritten digit im- ages for machine learning research [best of the web],","venue":null,"work_id":"463c40cc-af38-4d15-a3ea-25733755e704","year":2012},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.128138Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:73b3fea0cd77fecf2045922bd97e619fc9df8d29cb19625c8e639784bcd8501c","observation_id":"318d8425-bb6d-47ac-9e20-c1552e7b64c7","resolution":{"observed_at":"2026-08-12T13:40:10.381921Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-12T13:40:10.132794Z","title":"Gradient-based learning applied to document recogni- tion,","venue":null,"work_id":null,"year":1998},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.132794Z"},"links":{"citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:50396c3ee04d3b440f95ac031ea3cb785edb6d6ea82a127d059742d4ba206b6d","observation_id":"3b652df0-8d69-4c92-af02-3062233837e6","resolution":{"observed_at":"2026-08-12T13:40:10.132794Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1708.07747","last_updated":"2017-09-15T21:29:49Z","snapshot_observed_at":"2026-08-13T15:13:33.081929Z","submitted_at":"2017-08-25T14:01:29Z","title":"Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1708.07747","snapshot_observed_at":"2026-08-12T13:40:10.137269Z","title":"Fashion-mnist: a novel image dataset for benchmarking machine learning algorithms,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-12T13:40:10.137269Z"},"links":{"cited_paper":"/paper/1708.07747","citing_paper":"/paper/2411.16081"},"observation_digest":"sha256:5dfaac39bdba34b57de20f693bee7942779bc41343b310633a13aeaf53afd7a2","observation_id":"081a1284-42c9-4fe5-a17f-2bce01608ccf","resolution":{"observed_at":"2026-08-12T13:40:10.137269Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2411.16081","last_updated":"2024-11-25T04:22:17Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-15T06:41:06.276603Z","submitted_at":"2024-11-25T04:22:17Z","title":"Exploring the Generalization Capabilities of AID-based Bi-level Optimization"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":4,"verified_fuzzy":31},"total_outbound_references":49},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 1 inbound Pith citation observation for arXiv:2411.16081."}