{"as_of":"2026-08-19T23:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5d63d4984bc2a1fc84b0227603c0b52c180961a95d273db1ea33e4399aafc236","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:34:33.861676Z","state":"measured"},{"denominator":44,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":44,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2504.12503/citation-record","integrity":"/paper/2504.12503/integrity","json":"/paper/2504.12503/citation-record.json","paper":"/paper/2504.12503"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.374675Z","title":"A review of the artifi- cial neural network surrogate modeling in aerodynamic design,","venue":null,"work_id":"334d983e-dbae-4235-bd24-065c5da5195d","year":2019},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.698496Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:02e10c4ded6822e65ec444c771f0b71aa4142706d41f3fb2a05e5439e40eba0f","observation_id":"d5c2b62f-f6ad-48e6-bff4-f7d53800360b","resolution":{"observed_at":"2026-08-16T12:34:34.378256Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.364662Z","title":"Drivaer- net: A parametric car dataset for data-driven aerody- namic design and prediction,","venue":null,"work_id":"b6584ceb-6edf-4027-98a3-aca551bfb172","year":2025},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.703140Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:ec9d62d43c9e55443fb722c660cbf4287c8d30df817ee140d9b3c8335a30457f","observation_id":"f9684bac-82a1-4655-afb0-7010305de561","resolution":{"observed_at":"2026-08-16T12:34:34.368193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.353327Z","title":"Surrogate modeling of car drag coefficient with depth and normal renderings,","venue":null,"work_id":"0faddac7-39f7-4627-a814-27b68b2d9422","year":2023},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.707281Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:d3101d9543d6d3e94c40728d417a12e12760049c6b15480c95b3b23fd95aaf56","observation_id":"139fa037-979b-43fa-99c2-d153189f8dc7","resolution":{"observed_at":"2026-08-16T12:34:34.357534Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.342258Z","title":"Fast predictions of aircraft aerodynamics using deep- learning techniques,","venue":null,"work_id":"d8e171f6-544a-4194-88f2-40cbaabe137d","year":2022},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.711447Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:723fe17416c48929915af5f2142e2b3bfce96f9ca0b960d6ef561dd9ec440251","observation_id":"c9a75c1e-99cb-41f3-8a55-fb55247a888d","resolution":{"observed_at":"2026-08-16T12:34:34.346304Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.332161Z","title":"Data-driven design for metamaterials and multiscale systems: a review,","venue":null,"work_id":"a83202f4-9570-4ae9-b749-80014da8a0d6","year":2024},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.716452Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:66bb6740f315fd7eabf4538e30371c7e369a262413385f577b7cae781ebf2d8f","observation_id":"1d8f4e9b-b0b7-453f-b879-17ae8eafad56","resolution":{"observed_at":"2026-08-16T12:34:34.335646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.321520Z","title":"Digital twins: state-of-the-art and future direc- tions for modeling and simulation in engineering dy- namics applications,","venue":null,"work_id":"dc096823-abd0-462a-aeaf-8d6d9737d7fe","year":2020},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.720598Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:c35ac92bdb751665b5cbe2de67618cd12b501801cc53a2e6f6603cb6a941d787","observation_id":"0d29d190-357e-45e7-9c3f-41f4bbd46a05","resolution":{"observed_at":"2026-08-16T12:34:34.325345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.310717Z","title":"Industrial applications of digital twins,","venue":null,"work_id":"ab4c49d8-7290-4a66-a1cb-0e2d69233a8a","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.724937Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:8b552567f3b2b4c8867e961b7fba8c6c2f929e3f07db9f92b566c94a88353cd3","observation_id":"4fab3747-09a3-4195-bef5-e530d034ba6d","resolution":{"observed_at":"2026-08-16T12:34:34.314409Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.11908","last_updated":"2024-03-28T13:16:50Z","snapshot_observed_at":"2026-08-16T14:41:47.500694Z","submitted_at":"2023-11-20T16:40:29Z","title":"Continual Learning: Applications and the Road Forward","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.11908","snapshot_observed_at":"2026-08-16T12:34:33.728441Z","title":"Continual learning: Applications and the road forward,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.728441Z"},"links":{"cited_paper":"/paper/2311.11908","citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:1c8118dbeb74f10903b1629a9d0d19230239bd89773fd27164157d0235c39f7b","observation_id":"9bf48d16-01a2-44b0-b252-1b2fb2b353c4","resolution":{"observed_at":"2026-08-16T12:34:33.728441Z","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":"2026-08-16T12:34:34.300126Z","title":"A comprehensive study of class incremental learning algorithms for visual tasks,","venue":null,"work_id":"d1471798-8c29-4cf7-9fca-09aa907d99dd","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.732833Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:67e9f2e79e8ec3f24647e2d5be983abf4313415403a1ef551d3cd7177c6779a8","observation_id":"561b018f-7289-4c14-871e-c5df3e8e55ff","resolution":{"observed_at":"2026-08-16T12:34:34.303962Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.286944Z","title":"Class- incremental learning: survey and performance eval- uation on image classification,","venue":null,"work_id":"99c58cc2-c6b2-4c10-9f52-be90e1e64e74","year":2022},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.736467Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:4caceeef201dba95986a661b055b54e4b2bddadc921cf00dff18733458d2c105","observation_id":"2c8c50a9-60e9-404f-ba77-e22fa8011a47","resolution":{"observed_at":"2026-08-16T12:34:34.291079Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.273137Z","title":"Gradient-based learning applied to document recogni- tion,","venue":null,"work_id":"83499e3e-be14-439f-a948-d894fbd3f619","year":1998},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.740041Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:00f118632c1a836fa6cdb55c9f7fdd642a825b320f94d28119f3259a3736ddf9","observation_id":"27e0287d-2759-4cc3-8eb2-bc1a896406b2","resolution":{"observed_at":"2026-08-16T12:34:34.277573Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.261752Z","title":"Core50: a new dataset and benchmark for continuous object recogni- tion,","venue":null,"work_id":"8a4fb9a7-d771-40bb-aa3a-3708c4a0b92d","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.743652Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:c72f3a3f98d4cb11d95b236cfa9acf38243bdfd1a2168c05fb1eee4d9e4c2d5b","observation_id":"1e912abc-cd4d-4df8-b88b-eeaefd3a6cb9","resolution":{"observed_at":"2026-08-16T12:34:34.265484Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.249205Z","title":"Clear: An adaptive contin- ual learning framework for regression tasks,","venue":null,"work_id":"481f466b-314f-4b36-b8ed-788064ca813f","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.747022Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:0d1c522552e81f039f1a2b564e2a0540081da18dd684418e07e416a4e2405139","observation_id":"3d9e55e7-367d-47cd-adf0-c0c13296e2f2","resolution":{"observed_at":"2026-08-16T12:34:34.254348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.238654Z","title":"Three types of incremental learning,","venue":null,"work_id":"87f8a3d6-0d38-47d3-ba13-9f8b1fa762ae","year":2022},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.750234Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:a5384480a741ee93a9ed1e6fff3c30efb847635d2a0d520c6773f5db6322b00b","observation_id":"fa969a29-5884-4e3d-a020-a1b05d5cabff","resolution":{"observed_at":"2026-08-16T12:34:34.242200Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.227137Z","title":"Overcoming catastrophic forgetting in neural net- works,","venue":null,"work_id":"d09d65c6-6319-4f71-9aff-3222457ab847","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.753799Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:861b6edcc262ac6b032af55867a2208d16b8e7e64b37acff2987857b8f7a4ea4","observation_id":"06518032-4687-4c76-884b-ecff6c47cfc8","resolution":{"observed_at":"2026-08-16T12:34:34.231397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.216331Z","title":"P., and Wayne, G., 2019, Experience replay for continual learning","venue":null,"work_id":"b02fa6a6-766d-4faa-a8aa-f5086852ba1d","year":2019},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.757727Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:ef6531dce4b32d64d6ae069a15153ef70213d394e7363a84bf1413dac91b2ea5","observation_id":"145b4b2d-2bd8-4388-8ea8-aa6b6083cdaa","resolution":{"observed_at":"2026-08-16T12:34:34.219996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.205557Z","title":null,"venue":null,"work_id":"049954fd-6d03-480b-95ff-4934911598b9","year":2022},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.761884Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:79a19467a275ad5aa343cc540e5459c1aa0bd146e8b035c2383dbc827a9157a4","observation_id":"6542e5b2-516d-4a6f-a8eb-d4b2c3c493dd","resolution":{"observed_at":"2026-08-16T12:34:34.208980Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.194256Z","title":"A comprehensive survey of continual learning: Theory, method and application,","venue":null,"work_id":"f0a8e452-f2f3-4606-b798-706750692dc1","year":2024},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.765677Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:64554fb58a67584ffb345adf69e94843a364e334158c6935f8ecc9aa9d4fe166","observation_id":"33ccfcd9-f047-41ea-a429-8a3da706841f","resolution":{"observed_at":"2026-08-16T12:34:34.198172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.182720Z","title":"A continual learning survey: Defying forgetting in classification tasks,","venue":null,"work_id":"1c955faa-6aab-4489-85d4-11abac5db082","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.769278Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:9ebec267372ceaf9dd9dfe593e0165bef0b10c0ca549383144cb0d3180f1f1eb","observation_id":"3eae752e-e24e-4825-9141-17081604e2c9","resolution":{"observed_at":"2026-08-16T12:34:34.186626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.172350Z","title":"Embracing change: Continual learning in deep neural networks,","venue":null,"work_id":"ac1ee942-47b8-4478-b6fe-b5e2450b7b87","year":2020},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.772974Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:8d804518679557c2d85395effa9bef5875bb84d9d2d47456f0f7ebf89d73d889","observation_id":"1b73288c-8163-44d9-a02d-dafe9a002352","resolution":{"observed_at":"2026-08-16T12:34:34.176213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.161325Z","title":"Online continual learning in image classification: An empirical survey,","venue":null,"work_id":"38e20624-9f6f-43ed-835e-41477ba915ea","year":2022},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.776789Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:38c67a97fc980caefc24c6c848aba645c4bea9cbc1ad8756ca94051cee13e5c5","observation_id":"4a25b7a0-8d65-4b43-a2b7-bf17693c28e9","resolution":{"observed_at":"2026-08-16T12:34:34.165359Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2502.11927","last_updated":"2025-02-17T15:40:13Z","snapshot_observed_at":"2026-08-16T20:55:30.424333Z","submitted_at":"2025-02-17T15:40:13Z","title":"Continual Learning Should Move Beyond Incremental Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.11927","snapshot_observed_at":"2026-08-16T12:34:33.780147Z","title":"Con- tinual learning should move beyond incremental classi- fication,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.780147Z"},"links":{"cited_paper":"/paper/2502.11927","citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:4a7835ab66aab79b017bb9d2842f8de4aa763fad9b728608d279b392ea92449a","observation_id":"d061e6bb-ad99-42fa-9e0b-ab5df34f23b3","resolution":{"observed_at":"2026-08-16T12:34:33.780147Z","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":"2026-08-16T12:34:34.151328Z","title":"The clear benchmark: Continual learning on real- world imagery,","venue":null,"work_id":"dcf60e50-8424-4f36-9e0e-6e442e3f4f3f","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.783979Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:0473b68065f430437bf4d9b3e1d4855541a63d2b71b8d76b330c1f378043bc1c","observation_id":"ea4eeba1-d744-4f90-aa64-0153b0fbc9b8","resolution":{"observed_at":"2026-08-16T12:34:34.154993Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.139540Z","title":"Remind your neural network to pre- vent catastrophic forgetting,","venue":null,"work_id":"fcdc1236-0e80-43a8-8a24-838379bc20b8","year":2020},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.787526Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:383e3d9a449efce8a0991632aee07ed08d589a0f09f01fb10acce7be495b0868","observation_id":"145dd345-84f9-4094-b997-521652c4dea3","resolution":{"observed_at":"2026-08-16T12:34:34.143436Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.127468Z","title":"Online continual learning with maximal interfered re- trieval,","venue":null,"work_id":"dde57184-3367-4dfc-b565-46edd9066862","year":2019},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.790932Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:a68176811202f5296f52cf4be003267af6539a824fd3ad071e58291a3be1409a","observation_id":"5044c3be-758a-44c5-9d80-796050d915a5","resolution":{"observed_at":"2026-08-16T12:34:34.131363Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.116706Z","title":"Dark experience for general con- 17 Copyright © by ASME tinual learning: a strong, simple baseline,","venue":null,"work_id":"2cb33e33-6408-4bec-9e38-3a8ea6ea14ab","year":2020},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.794325Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:8db6d735dbd40bd708331835e483dd0e9d9ae3a76ebb41fb801e5475162ef58b","observation_id":"b920109b-0a47-4688-9291-cdc8a36684ce","resolution":{"observed_at":"2026-08-16T12:34:34.120511Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.106326Z","title":"Con- tinual learning through synaptic intelligence,","venue":null,"work_id":"0718ada2-38c8-4902-b8df-65771eb6c89f","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.797649Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:e18d09eeb3e92cd98bba65166d25cd2e6fba159950d99de8b7d3f092bd2c241d","observation_id":"bb715340-d39e-4bde-8bb0-222319444895","resolution":{"observed_at":"2026-08-16T12:34:34.109944Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.092122Z","title":"Memory aware synapses: Learning what (not) to forget,","venue":null,"work_id":"d32e8aac-ae1c-4a78-b8a9-3d97da9e60e5","year":2018},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.801647Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:daee90ed3adecf6986fd9157f2a25c4dc3a8bb24c05c9841f654aae0e46fd870","observation_id":"8b7094c2-6c16-40c9-b3de-ca936cf1d736","resolution":{"observed_at":"2026-08-16T12:34:34.097421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.078695Z","title":"Learning without forget- ting,","venue":null,"work_id":"8394794b-5b07-46de-a199-efa27b20a521","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.805150Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:6c65d71fef8aa250b9f7722763c3635d7937cfa1bb64cd37d23cdccf93f42422","observation_id":"a52e59c4-895f-4e35-927d-3f4f3f1e77f7","resolution":{"observed_at":"2026-08-16T12:34:34.083753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.067129Z","title":"icarl: Incremental classifier and repre- sentation learning,","venue":null,"work_id":"47450699-4759-41e0-acec-468c4ace48c0","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.808791Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:f248da806e4187b366bb0fb53bb31753e172f8cea9c6b91977ba141c3ac5a9b5","observation_id":"4b82c035-0f2d-49ab-a725-78a627423e5d","resolution":{"observed_at":"2026-08-16T12:34:34.071583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.055962Z","title":"Op- timal continual learning has perfect memory and is np- hard,","venue":null,"work_id":"6835a162-40bf-4f8a-a9b3-12007e17f83d","year":2020},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.812207Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:1f9aa098368e911176f2a6fadad279d94280065562c3812135a1ef5a26c9321d","observation_id":"af588389-ecf6-4ea5-a66e-e05948724eca","resolution":{"observed_at":"2026-08-16T12:34:34.060460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.044279Z","title":"Continual learning for neural regression networks to cope with concept drift in industrial processes using convex optimisation,","venue":null,"work_id":"c47a1c8a-f155-4100-8c64-fa9abf672148","year":2023},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.815506Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:cc6ea1529be542687c1a5011ed9102fbd36c347e1df7556066e0636e415f216e","observation_id":"da6c59e1-561e-4686-b85f-fa88ef5cdb2f","resolution":{"observed_at":"2026-08-16T12:34:34.048255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.06418","last_updated":"2025-03-16T01:55:58Z","snapshot_observed_at":"2026-08-16T13:11:19.806851Z","submitted_at":"2024-10-08T23:12:33Z","title":"MIRACLE3D: Memory-efficient Integrated Robust Approach for Continual Learning on Point Clouds via Shape Model Construction","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06418","snapshot_observed_at":"2026-08-16T12:34:33.818928Z","title":"Miracle 3d: Memory-efficient integrated robust approach for con- tinual learning on point clouds via shape model con- struction,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.818928Z"},"links":{"cited_paper":"/paper/2410.06418","citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:1cac109532e22596aeb15dd975e97f1782e50a71f23b889bb2b36ba6fa72984a","observation_id":"6a847d83-dca4-411c-b3d9-5d524c59851a","resolution":{"observed_at":"2026-08-16T12:34:33.818928Z","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":"2026-08-16T12:34:34.032460Z","title":"Continual learning in 3d point clouds: Employ- ing spectral techniques for exemplar selection,","venue":null,"work_id":"9c92c69b-28fd-44b9-b889-78e381dd0851","year":2025},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.822859Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:f1ed45c78f8f223dd8dea4c05ea99d10dd0d3a600ec5d01cf927ed6b99b9e38f","observation_id":"73fa8d34-9ea6-495b-a0f4-ecfd92c6cf06","resolution":{"observed_at":"2026-08-16T12:34:34.037010Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.022192Z","title":"On the use of surrogate models in engi- neering design optimization and exploration: The key issues,","venue":null,"work_id":"f02d07e1-ce4a-4fba-8326-d12664381e22","year":2019},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.826487Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:f17184b8d851e176a4b84242ff5d6eee33a3a4f7481179aae23cd6d1ec2d2255","observation_id":"ebf68ab1-d5dd-48b1-ab34-c3cb80d9b3f2","resolution":{"observed_at":"2026-08-16T12:34:34.025930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.011891Z","title":"Practitioners guide to mlops: A framework for con- tinuous delivery and automation of machine learning,","venue":null,"work_id":"3dfa37f9-9298-48c6-b16b-341963eda5e9","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.830225Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:80f377c80dd2147836483e448ea7ef953411a94694c072198d7af6d3f84c9825","observation_id":"60137b9a-0a13-4792-9bf4-db6fbeac100f","resolution":{"observed_at":"2026-08-16T12:34:34.015514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:34.000886Z","title":"Ship-d: Ship hull dataset for design optimization using machine learning,","venue":null,"work_id":"b4d0b602-5ba4-4e8c-9450-b6a5045e9937","year":2023},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.833698Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:a6fce3fbbe01ea447c21f34399ca87c09a40fbb2e3c1b67a330bb8bb6dde2c38","observation_id":"08ae7033-5d69-4d3a-8d61-0f11f1f1e6fc","resolution":{"observed_at":"2026-08-16T12:34:34.005204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.990600Z","title":null,"venue":null,"work_id":"abbdc7ae-bf55-408e-ba20-389b33cebb82","year":2024},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.837605Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:fe9e31ef379b6bb27a2f9ec397ac2cee90aba97f56bc2b2900409acd246b9573","observation_id":"7c1e68af-ba71-4d68-a39c-737842b69a7a","resolution":{"observed_at":"2026-08-16T12:34:33.994279Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.979544Z","title":"Drivaernet++: A large-scale multimodal car dataset with computational fluid dynamics simulations and deep learning benchmarks,","venue":null,"work_id":"15301c9d-ce5c-43e2-abaa-0f40b490dbd9","year":2025},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.841432Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:ba307111b2514b9c2070658637a8e7700fa0cc31a30c3141218325184e07d67c","observation_id":"1adc4806-0d40-4f2e-93e2-09701a369129","resolution":{"observed_at":"2026-08-16T12:34:33.983571Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.967819Z","title":null,"venue":null,"work_id":"6304cda1-c9f7-4577-beec-4447ed26a933","year":2024},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.845115Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:8be6de1759cd51a5b666696ffc7a5ef9515c0eb115a76b19ec18f990ab47efca","observation_id":"45451bc6-7a3f-419c-8a82-1dadbc4fb615","resolution":{"observed_at":"2026-08-16T12:34:33.971844Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.954662Z","title":"Pointnet: Deep learning on point sets for 3d classi- fication and segmentation,","venue":null,"work_id":"fd038adc-e7a0-4e67-97c6-2bd96985516b","year":2017},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.849056Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:ee505a1bca2abe83063840e7fe5c9364c83bbec0d26c29de83da9321aaa597a3","observation_id":"3b85c7e4-f981-4d0c-9a6d-71b1be5be0c8","resolution":{"observed_at":"2026-08-16T12:34:33.958753Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.943446Z","title":null,"venue":null,"work_id":"2ef686d4-ffba-4350-8563-e176f73b1b89","year":null},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.852951Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:e0a39d52772fcc36b342d661552395af2fb9bc85d4412869fe5142c7e1819434","observation_id":"def76dca-d9e5-4c2b-a0da-c7cac8bf6dad","resolution":{"observed_at":"2026-08-16T12:34:33.947395Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.932723Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":"11b22c5d-5ecb-4ae4-afdd-3b33267780f0","year":2016},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.857981Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:b08f581cd7c120c72f1074e7feedfd117f2a8450b10b31923621118fb653b6da","observation_id":"3bc3c37a-ab56-46c7-8ac1-8211e3e08d59","resolution":{"observed_at":"2026-08-16T12:34:33.936499Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T12:34:33.919674Z","title":"Avalanche: an end-to-end library for continual learn- ing,","venue":null,"work_id":"008699f0-9d8b-45eb-9460-e5a3ec745daf","year":2021},"citing_paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T12:34:33.861676Z"},"links":{"citing_paper":"/paper/2504.12503"},"observation_digest":"sha256:52c4662f7e1a432805b62a0500e54d10df71f879b5df09c85004276290046a90","observation_id":"bcb97f69-f888-4e1c-9a9b-a4fe7d7a3c05","resolution":{"observed_at":"2026-08-16T12:34:33.925331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.12503","last_updated":"2025-04-16T21:40:03Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-19T13:30:31.208786Z","submitted_at":"2025-04-16T21:40:03Z","title":"Continual Learning Strategies for 3D Engineering Regression Problems: A Benchmarking Study"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":37},"total_outbound_references":44},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 0 inbound Pith citation observations for arXiv:2504.12503."}