{"as_of":"2026-08-08T00:43:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:729a6cdaf61c55c8f2755bd08f3ce659d9da36ba4e592a38a76190c67306040f","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:02:45.639207Z","state":"measured"},{"denominator":47,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":47,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.09174/citation-record","integrity":"/paper/2506.09174/integrity","json":"/paper/2506.09174/citation-record.json","paper":"/paper/2506.09174"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.465090Z","title":"Tfb: Towards comprehensive and fair benchmarking of time series forecasting methods","venue":null,"work_id":"065e9079-6f37-4056-9f5d-a9f1a4eadbd1","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.445967Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:4cc13997d60286de49e58ab9e131ac813ae491c4d1905695d142c095b6edea58","observation_id":"06decba2-834c-40a1-bdef-e7c5eb7ed69c","resolution":{"observed_at":"2026-08-07T05:02:46.469456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.451139Z","title":"Timemixer++: A general time series pattern machine for universal predictive analysis","venue":null,"work_id":"bf5af533-66e2-4fcb-9f92-9c6fada44f13","year":2025},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.450878Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:3163b7d757f2ba2af3e32e419c20a037664f595de5e3ec4c3011e67e4748325d","observation_id":"defca2b3-4875-4d9d-b080-b94556a5bcdb","resolution":{"observed_at":"2026-08-07T05:02:46.455635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.437159Z","title":"A machine learning model for hub-height short-term wind speed prediction.Nature Communi- cations, 16(1):3195, 2025","venue":null,"work_id":"d220e24b-43cd-4814-a5bf-754b756840dd","year":2025},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.455397Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:5ae259bec42e800c79d9e5155841bcb9704b8dcd010ffd3a4c97b7ea0c2be3f0","observation_id":"dcbc5373-e832-44be-9ac3-6eec89267623","resolution":{"observed_at":"2026-08-07T05:02:46.441456Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.423001Z","title":"Fourcastnet: A global data-driven high-resolution weather model using adaptive fourier neural operators","venue":null,"work_id":"4bc52222-199f-4859-903e-53693fd9079b","year":2022},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.459914Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:f2451ec7864c82d23c597e138ab425661df650b89fd7a99c5b0fa08d0b42bff9","observation_id":"5f867787-db29-42f9-bf51-dad43103b3c2","resolution":{"observed_at":"2026-08-07T05:02:46.427513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.408324Z","title":"Accurate medium-range global weather forecasting with 3d neural networks.Nature, 619(7970):533– 538, 2023","venue":null,"work_id":"80bfc89d-0144-4768-8b17-b67c171df39a","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.464738Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:c18ca5a699621b452b5130e5786ea8edd880c18518d49b3a78e5c8440d0bec04","observation_id":"a86d8ded-9991-4e37-a7da-5cc0089bc9e7","resolution":{"observed_at":"2026-08-07T05:02:46.412804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.394477Z","title":"Informer: Beyond efficient transformer for long sequence time-series forecasting","venue":null,"work_id":"881acfa7-0623-458d-9a54-ed3fdf6a100b","year":2021},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.469298Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:672315792be240017ad4ea341f3e925ea71241025c0a80f0d982c4137900670e","observation_id":"77c7dcf9-59b4-43bb-ba7a-3a4976a69456","resolution":{"observed_at":"2026-08-07T05:02:46.398864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.380536Z","title":"Forecasting at scale.The American Statistician, 72(1):37–45, 2018","venue":null,"work_id":"156809b0-f75a-4161-b456-241ddd6ec049","year":2018},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.473866Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:7a75eb39e7a511cf7d82443c68d4100a0686384690ac7c6430a313aa8680413f","observation_id":"9b9ae189-a153-4a51-ab82-481b2ff214a2","resolution":{"observed_at":"2026-08-07T05:02:46.384906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.366689Z","title":"N-beats: Neural ba- sis expansion analysis for interpretable time series forecasting","venue":null,"work_id":"2ee6e2de-7bf8-4ffc-8502-249720f38717","year":2020},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.478124Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:d8b4fa78addacbdf53070e7701b33ec99fcce0373597c38c90597d781a46d3cb","observation_id":"22cced5c-51cf-49a8-b790-ab132de68e59","resolution":{"observed_at":"2026-08-07T05:02:46.371000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.352307Z","title":"Peri- odicity decoupling framework for long-term series forecasting","venue":null,"work_id":"5f3b8979-3ca4-4c88-b7cf-14f6617a1d94","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.482052Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:9a84c2937b80e6909a1c0631e01ef9d2163cb503cd341ee5fab392cf6949bd11","observation_id":"c8ea230f-a781-4552-bbae-d14f86ddf294","resolution":{"observed_at":"2026-08-07T05:02:46.357019Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.338553Z","title":"A time series is worth 64 words: Long-term forecasting with transformers","venue":null,"work_id":"62786c90-c3ac-4719-94eb-520f7e0ae8d4","year":2022},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.486322Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:7f29a6b8d2bdcf43fa38b1684fe2f2d90003c390cef6d349fbcf5bfbe92eae7f","observation_id":"ea3f641e-aacd-407d-9b46-b3d23c1640cf","resolution":{"observed_at":"2026-08-07T05:02:46.342813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.324581Z","title":"Multi- resolution time-series transformer for long-term forecasting","venue":null,"work_id":"a34ef24b-9c7d-4c6a-a0a8-d0bfd2305557","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.490187Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:459d71a36085237b1795c4754e1466c8332cede305d087f811055b65f6e49a81","observation_id":"8ef0492d-8f62-4345-91e3-70546a89d586","resolution":{"observed_at":"2026-08-07T05:02:46.328721Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.310670Z","title":"Attention is all you need","venue":null,"work_id":"dffe8c4d-d792-47c2-8cea-ffcd34f0e3b0","year":2017},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.494117Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:c81984a39dca57e0e480a2b10c8e09f9157daab28e6f88ec00de206d2aad6087","observation_id":"1f0c3494-e411-49b8-98a6-3898b921ad29","resolution":{"observed_at":"2026-08-07T05:02:46.314779Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.296086Z","title":"Timesnet: Temporal 2d-variation modeling for general time series analysis","venue":null,"work_id":"255d0852-86d9-4c20-b8db-a7bb5da8df24","year":2022},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.498462Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:8ee0a68c52ad8818834f7425b1913d719769de303f58fa48c5e4777c7930508a","observation_id":"bb4747c5-2ddf-4cb3-a19e-25aa73fb63d3","resolution":{"observed_at":"2026-08-07T05:02:46.301086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.281456Z","title":"Moderntcn: A modern pure convolution structure for general time series analysis","venue":null,"work_id":"821f61ab-cb68-4467-bc38-3fe84d03036c","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.502627Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:7f09cf69b4f4ae7092e627b2d4e77f71b56836d8ec78aada4855827da955858f","observation_id":"ab1458b9-c25b-4de9-aac4-6970380eeba3","resolution":{"observed_at":"2026-08-07T05:02:46.286136Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.267161Z","title":"Are transformers effective for time series forecasting? InProceedings of AAAI Conference on Artificial Intelligence (AAAI), 2023","venue":null,"work_id":"66b81aa7-d74c-4b99-b30e-e13649e8ae8d","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.506526Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:048b8d2f2c17897cc1d630dd5170fcb411ee99589275679d2a2e876d0cd12229","observation_id":"29a645ed-380a-4871-ac4e-d55ed0bcedba","resolution":{"observed_at":"2026-08-07T05:02:46.271701Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.251965Z","title":"Fourier neural operator for parametric partial dif- ferential equations","venue":null,"work_id":"e95d9c2a-7c05-43c3-ae5b-07e8a5a20ecb","year":2021},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.510445Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:ddb1c5c2a39fa8ec572608305f7d5677bc7fadbc2ea1fadffd35876b633e451d","observation_id":"c3708941-a6fe-4683-b013-fc64fc9e3f9e","resolution":{"observed_at":"2026-08-07T05:02:46.257375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.236514Z","title":"Adaptive fourier neural operators: Efficient token mixers for transformers","venue":null,"work_id":"b4ce9d02-2906-4be3-a9d8-34ff507a3f0a","year":2022},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.514236Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:07a5eee3f809a64b56a5e58627fb904cab2b2ef29eb5b500be52e64c832a48ec","observation_id":"7146493e-a6e4-4e4b-beda-0cd208b1b86f","resolution":{"observed_at":"2026-08-07T05:02:46.241421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.222090Z","title":"Crossformer: Transformer utilizing cross-dimension depen- dency for multivariate time series forecasting","venue":null,"work_id":"5af1eb55-a67b-429c-b1c1-e639a4399d36","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.518253Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:8d57ffaae94d48fca2b666705b0c09ad8e997f09b94aa45f692d2ef5c40b5d6d","observation_id":"41c455b0-033c-4abd-b633-f23853c2c56c","resolution":{"observed_at":"2026-08-07T05:02:46.226840Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.208102Z","title":"From similarity to superiority: Channel clustering for time series forecasting","venue":null,"work_id":"fccc5e5b-bfad-49e4-8a8f-f5ce90c1253c","year":null},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.522286Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:566c270e841fd669caf8b323ffe7662f6669ec60fb0b85654213f9ad46db7273","observation_id":"b3403d1e-5bcb-41c2-8058-a3db024d8717","resolution":{"observed_at":"2026-08-07T05:02:46.212777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.193962Z","title":"Deep learning and the information bottleneck principle","venue":null,"work_id":"13a863a8-7c48-4f46-8166-7e9f66443f63","year":2015},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.526869Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:dc9547a77c28487e6e8e37e22de21289fe7a1d466da6113d190835f594c7cdea","observation_id":"77378611-51f6-4544-86a2-50bdacaaae68","resolution":{"observed_at":"2026-08-07T05:02:46.198290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.180249Z","title":"Pathformer: Multi-scale transformers with adaptive pathways for time series forecasting","venue":null,"work_id":"bf5374d2-5771-4efc-b185-2ef77738e936","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.530973Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:658e73a387145f2a82f8927f4d5a4c0267ce765680ecce7188ce3230a1893aad","observation_id":"55303877-fea8-46a5-be7b-75017a3c8287","resolution":{"observed_at":"2026-08-07T05:02:46.184449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.166156Z","title":"Deep adaptive input normalization for time series forecasting.IEEE Transactions on Neural Networks and Learning Systems, 31(9):3760–3765, 2019","venue":null,"work_id":"f7bedc37-b73e-4060-a485-8498906e982a","year":2019},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.535042Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:f31ee9011aad7a1177b22f12c4b1cc9a180b218d9578025aa6d9f7d153302a00","observation_id":"09778e9a-17b0-4b23-a3e5-aaebb417de10","resolution":{"observed_at":"2026-08-07T05:02:46.170971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.151898Z","title":"Ddn: Dual-domain dynamic normalization for non-stationary time series forecasting","venue":null,"work_id":"5629b30d-cc7f-40d8-a0ce-08d4ea9637a8","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.539021Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:b2c6a61c17f2bc0ab091916d61b34fd5e68c71fed335e9e6c6b2b8b0622f2ded","observation_id":"3925d1fc-a11b-410e-a800-ba8876b7849b","resolution":{"observed_at":"2026-08-07T05:02:46.156148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.138107Z","title":"Time- bridge: Non-stationarity matters for long-term time series forecasting","venue":null,"work_id":"70e1d779-08fa-410f-a048-f32cc3fae367","year":2025},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.542987Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:cc77bcb048bdfd91aa0673d4b20d02af2e93ae943c178696f512e610047ce793","observation_id":"c6e2205d-01b7-4f17-855b-024f8870e7b2","resolution":{"observed_at":"2026-08-07T05:02:46.142269Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.10721","last_updated":"2026-05-17T02:25:14Z","snapshot_observed_at":"2026-08-03T04:41:00.104637Z","submitted_at":"2023-05-18T05:39:46Z","title":"Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.10721","snapshot_observed_at":"2026-08-07T05:02:45.546915Z","title":"Revisiting long-term time series forecasting: An investigation on linear mapping.arXiv preprint arXiv:2305.10721, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.546915Z"},"links":{"cited_paper":"/paper/2305.10721","citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:905a68bd15ee791638daff08bab4ebf714442b96d1e92f9ddfbac1c67d0589ce","observation_id":"98cb6a1a-f0b1-4096-9fb9-d84c01e93274","resolution":{"observed_at":"2026-08-07T05:02:45.546915Z","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":"2026-08-07T05:02:46.123651Z","title":"Reversible instance normalization for accurate time-series forecasting against distribution shift","venue":null,"work_id":"f5fa31d1-6ab1-458b-98b7-e908c344ab5a","year":2021},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.551429Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:05b247218eb5162eeb6f6bb04b7907554bd044a988cd2acbd0b21dfa06744d70","observation_id":"2c55a229-6a82-456a-87ba-420a003d5ed2","resolution":{"observed_at":"2026-08-07T05:02:46.128581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.109742Z","title":"Dish-ts: A general paradigm for alleviating distribution shift in time series forecasting","venue":null,"work_id":"12f98aef-266d-4a25-9f72-fa2e917679be","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.555588Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:2268c70323174b996c707a4a7296eee7bc615ea33ea2b9ad91aca29048d3fc9e","observation_id":"7f888c6c-36fb-4f3b-aab9-f0023e54b232","resolution":{"observed_at":"2026-08-07T05:02:46.114106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.092433Z","title":"Adaptive normalization for non-stationary time series forecasting: A temporal slice perspec- tive","venue":null,"work_id":"6b5312ba-4e26-4186-9bf5-f69d856be79b","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.559632Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:e8d2089adf6c059793c7e1098c24d9725782021a7fbe274cd23bcdd1995fea7c","observation_id":"9481ba6d-34fe-47f1-8f7d-b5397fd2dbdf","resolution":{"observed_at":"2026-08-07T05:02:46.097303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.077589Z","title":"Frequency adaptive normalization for non-stationary time series forecasting","venue":null,"work_id":"929198d2-ea73-413a-ab85-9cc0bb904b25","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.564148Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:3dd7260de5404d22b5352ee303336437266a7fb58c213c172904252934d80602","observation_id":"c0d7be63-bfa2-415c-9cac-24d763d657f3","resolution":{"observed_at":"2026-08-07T05:02:46.082062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.064027Z","title":"Prformer: Pyramidal recurrent trans- former for multivariate time series forecasting","venue":null,"work_id":"75765b71-2a0a-4078-b409-3ae43539e1bc","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.568326Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:3915a67215ede3b3fc7d331e3688bd2b20c595abb1c960445ea5db9738e1804a","observation_id":"a52ceb38-0edb-4fab-9fc7-bde7ce1c1783","resolution":{"observed_at":"2026-08-07T05:02:46.068210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.050073Z","title":"Learning to embed time series patches inde- pendently","venue":null,"work_id":"590db234-8346-4fb5-b995-656de0e2511f","year":null},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.572703Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:bc5dfa1e640b93c8231e04e56ca679a05c4a0b9a97b27e5424124283ce9b9bef","observation_id":"fad5a55a-5ac2-45c0-ae6a-74c30bc7136e","resolution":{"observed_at":"2026-08-07T05:02:46.054795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.035590Z","title":"Hdmixer: Hierarchical dependency with extendable patch for multivariate time series forecasting","venue":null,"work_id":"deb6bd38-2004-4611-b2dc-ea8b7762009d","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.576964Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:de12a841e621cbc2199132d0cf78b6ff7d2dd2b19c9306bfb65c4e92b3f97fca","observation_id":"a7b67246-8363-4e55-8b75-4f3fbb8694ba","resolution":{"observed_at":"2026-08-07T05:02:46.039916Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.020751Z","title":"Autoformer: Decomposition trans- formers with auto-correlation for long-term series forecasting","venue":null,"work_id":"c8173175-88a1-455f-b93a-ba410ad018af","year":2021},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.581152Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:d5bfa9fb75840bf70fb9b464d5b6cf647634d8b09e0d77c714ea9b271fc954ac","observation_id":"a41ef9a6-7a1d-4cfd-ab33-455292d3f246","resolution":{"observed_at":"2026-08-07T05:02:46.025301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:46.006475Z","title":"A decoder-only foundation model for time-series forecasting","venue":null,"work_id":"5732e64f-3f30-4c41-bced-cb1259984ca4","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.585145Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:dd1272e527b5e7a524bb4b459e5729a1006f3b58ad25551504d12a83aab7bc0d","observation_id":"09a46f08-25c5-4fc2-85de-5097638429a8","resolution":{"observed_at":"2026-08-07T05:02:46.011163Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.991429Z","title":"Time-moe: Billion-scale time series foundation models with mixture of experts","venue":null,"work_id":"ce936e53-f407-4379-8c29-e0261671eb9e","year":2025},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.589171Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:4778217f37b2f14ee9e93c46d9b3f72213b3828d7f8c3e97a649f3640a662a90","observation_id":"4e0eaa92-3743-4d2b-a854-8c491565e582","resolution":{"observed_at":"2026-08-07T05:02:45.996766Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.976495Z","title":"Fredf: Learning to forecast in frequency domain","venue":null,"work_id":"4a1ca98c-f593-4b16-9ac8-cf66777a02b2","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.593241Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:5589b189038d91345cf9da4dbea4bf57e7d7645fda210068fe24605f899802af","observation_id":"fe9be900-09e1-4d26-be5f-5b8bb2d98f8d","resolution":{"observed_at":"2026-08-07T05:02:45.981607Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.962169Z","title":"Rectified linear units improve restricted boltzmann ma- chines","venue":null,"work_id":"71dd5c1b-979a-46cb-9062-76605fa8d2e6","year":2010},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.597529Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:cc0725668ce1c4cfe5bcd913dd250a1c6bed3f90c37498e80e59a5a481bfbf76","observation_id":"00cf3c56-d1ec-451e-ab33-e2752afcba40","resolution":{"observed_at":"2026-08-07T05:02:45.966593Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.08415","last_updated":"2023-06-06T01:53:32Z","snapshot_observed_at":"2026-07-06T05:01:27.910364Z","submitted_at":"2016-06-27T19:20:40Z","title":"Gaussian Error Linear Units (GELUs)","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.08415","snapshot_observed_at":"2026-08-07T05:02:45.601801Z","title":"Gaussian error linear units (gelus).arXiv preprint arXiv:1606.08415, 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.601801Z"},"links":{"cited_paper":"/paper/1606.08415","citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:08da4f1f4bc1bd7689a287b41924792b321811fb82c8413e5f18a5885a27b206","observation_id":"b1c4605c-f55b-435c-bf38-094256721f70","resolution":{"observed_at":"2026-08-07T05:02:45.601801Z","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":"2026-08-07T05:02:45.947336Z","title":"De-noising by soft-thresholding.IEEE Transactions on Information Theory, 41(3):613–627, 2002","venue":null,"work_id":"97e0a5d2-b0bf-4d2d-984e-534b8268fd69","year":2002},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.606244Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:20a2af0fce33ccf43cffabdcdf22a59ffeed3b5cf937838874b4d51051636fc9","observation_id":"c7703718-98e0-43aa-9126-e88ccd394ad7","resolution":{"observed_at":"2026-08-07T05:02:45.951692Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.933077Z","title":"Deep variational infor- mation bottleneck","venue":null,"work_id":"1fc96779-be56-49ad-aebf-be2758d8160c","year":2017},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.610230Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:80e5041e36b48dc90bf9835f3994ea5f4a15086e3333fca0f5f16d4452478d00","observation_id":"d98b60af-f5ae-4cfa-94e1-0a4ca6b00c19","resolution":{"observed_at":"2026-08-07T05:02:45.937630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.918196Z","title":"Non-local neural networks","venue":null,"work_id":"fae10e84-ab55-470e-9d30-50f126056aea","year":2018},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.614295Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:44e07b0acdbe3c24eff4d30ff6c9f6a72b32f583394ad92b02c1305642b375b5","observation_id":"7af6945b-3874-4ccd-9be0-65fe79e1bc2a","resolution":{"observed_at":"2026-08-07T05:02:45.922907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.902991Z","title":"Learning representations by back-propagating errors.Nature, 323(6088):533–536, 1986","venue":null,"work_id":"2bdf88df-adf3-40db-bdff-7c3b71582caf","year":1986},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.618310Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:e1a6f9f7d22d5b6dea67978a481c2b661138f7cb7be46d1903a37d99e0d55878","observation_id":"c988bd71-0b62-48e6-b36f-e224b03d6ebc","resolution":{"observed_at":"2026-08-07T05:02:45.907390Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.888335Z","title":"itransformer: Inverted transformers are effective for time series forecasting","venue":null,"work_id":"2365b99f-21de-470e-97b5-52487ece36af","year":2023},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.622404Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:b87bfebfbc2bff54188a0e38360de9877acb55a5b141ca29f7133b2c8a06bc11","observation_id":"de75b8e3-b5f3-442c-b5af-4c23366e1031","resolution":{"observed_at":"2026-08-07T05:02:45.892776Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.873717Z","title":"Zhang, and Jun Zhou","venue":null,"work_id":"061d6ecd-fd17-4737-b80f-aa9f43e67ba7","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.626576Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:94c09e46ce4acdca4695b708c7bfd7f766e6df9ac41ef0a20c6ce098fc16a40f","observation_id":"dec64eba-4fca-4b5b-9dd5-1f8bd3eede17","resolution":{"observed_at":"2026-08-07T05:02:45.877976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.858294Z","title":"Mamba: Linear-time sequence modeling with selective state spaces","venue":null,"work_id":"947cdf0c-3c85-4f31-84a4-2945d43662d6","year":2024},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.630900Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:c311a868f7a73119b503e5413c4b6b6715e1a754744d4d82ba7baad252856e99","observation_id":"427899d7-bbdb-4396-a952-60e3ae5c944d","resolution":{"observed_at":"2026-08-07T05:02:45.863374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.843770Z","title":"Cautionary tales on air-quality improvement in beijing.Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 473(2205):20170457, 2017","venue":null,"work_id":"1bb5bb0a-ff05-4226-845b-6e4b051b084a","year":2017},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.634895Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:0f9f9b2666621f576cd5d75dad49a3e4952e7c6921883a8ea0a10661990eec0c","observation_id":"ef2dc597-e1cd-4279-916a-d1c1ffd904cc","resolution":{"observed_at":"2026-08-07T05:02:45.848393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"3710.3920","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:02:45.791764Z","title":"Global transpiration data from sap flow measurements: the SAPFLUXNET database.Earth System Science Data Discussions, 2020:1–57, 2020","venue":null,"work_id":"2b1b8fbf-0d2e-4dde-957f-bc31996d4dae","year":2020},"citing_paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T05:02:45.639207Z"},"links":{"citing_paper":"/paper/2506.09174"},"observation_digest":"sha256:014d4b0947c3b9ba502c057f40191606f81f1a35afaf9d8f1545fd3397230d9d","observation_id":"1ffbb981-63b0-431b-be20-2cac7e2454ce","resolution":{"observed_at":"2026-08-07T05:02:45.801658Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.09174","last_updated":"2025-09-12T09:50:48Z","latest_version":2,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T04:53:02.906405Z","submitted_at":"2025-06-10T18:40:20Z","title":"Multivariate Long-term Time Series Forecasting with Fourier Neural Filter"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":2,"verified_exact":1,"verified_fuzzy":44},"total_outbound_references":47},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 0 inbound Pith citation observations for arXiv:2506.09174."}