{"as_of":"2026-08-15T20:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:475c8cb1f8fbb295876904d92ef47a5f99705b854f28a3089e443faade5d144c","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:52:02.770061Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/2505.20716/citation-record","integrity":"/paper/2505.20716/integrity","json":"/paper/2505.20716/citation-record.json","paper":"/paper/2505.20716"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T13:52:10.411605Z","title":"Edformer: Embedded decom- position transformer for interpretable multivariate time series predictions, 2024","venue":null,"work_id":"72b16392-1788-454a-8444-ca8f2258fa4c","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:58.830578Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:c33cda5a5941a9f5b7a4818f5cc43139db1470b6e5e66f75fe0190a12e478257","observation_id":"7eaf29eb-03b9-4949-b4a7-a016f6574ff9","resolution":{"observed_at":"2026-08-07T13:52:10.483872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:10.256722Z","title":"Con- tiformer: Continuous-time transformer for irregular time series modeling","venue":null,"work_id":"a57cb16b-b0f5-41b8-8b58-68fda716d6a6","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:58.917702Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:dc4b927117f4ec1d58c760b8401c5b61197aa437b9cdb3fe484a29e29244df4c","observation_id":"b9806b6c-475a-41bc-a0d5-469754f93842","resolution":{"observed_at":"2026-08-07T13:52:10.319129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:10.110402Z","title":"Pe- riodicity decoupling framework for long-term series forec asting","venue":null,"work_id":"06ff0fde-6765-4ebf-add8-b0f6fbdb2862","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.034037Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:e6ee980d4f6c3d1be85aafd2940db45297c4efd387dea63043e5c5cc18bad79b","observation_id":"32c224c7-3d83-4e28-9607-f8d5c661f036","resolution":{"observed_at":"2026-08-07T13:52:10.178602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:09.763143Z","title":"Pe- riodicity decoupling framework for long-term series forec asting","venue":null,"work_id":"7fc4029d-8244-44b4-b0ba-af2a039029bf","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.138435Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:3eb7bc91361aaf65d671acbcbe194f9005df31142f96b410125882c371968d39","observation_id":"244e7393-3f9d-422e-9fa4-4d6238979967","resolution":{"observed_at":"2026-08-07T13:52:09.963125Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:09.382876Z","title":"SOFT S: Efﬁcient multivariate time series forecasting with series-core fusion","venue":null,"work_id":"d1103f71-2808-4dfb-a3fd-cc165d4874af","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.252529Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:5abb379f63957e4ad55ed9953c30fd25f90352d344918fe5aa31ede683634fd8","observation_id":"0b106115-2239-4068-85a8-8b4852340fb2","resolution":{"observed_at":"2026-08-07T13:52:09.599863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:09.139102Z","title":"WITRAN: Water-wave information transmission and recurrent accele ration network for long-range time series forecasting","venue":null,"work_id":"9912ccc8-f224-4ff3-b61f-4ef1b4a49264","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.370177Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:d4b2c7c9326613971fe707c9995b4ac72469ec849c95eed4eba31ea4fe744616","observation_id":"d2d728dd-df4a-4a49-b8c1-eabc6d3e4c48","resolution":{"observed_at":"2026-08-07T13:52:09.258279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:08.765558Z","title":"Zha ng, Xiaoming Shi, Pin-Y u Chen, Y uxuan Liang, Y uan-Fang Li, Shirui Pan, and Qingsong Wen","venue":null,"work_id":"5c60a681-5c05-4cb3-885a-21513f758cdd","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.464751Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:4ac22f5472801d4f4efb6a7a8709711fced2e2a5fd3d9eaf2d0287c0b870fee6","observation_id":"36f48da8-783e-4945-a606-b67f0fa13eb5","resolution":{"observed_at":"2026-08-07T13:52:08.992971Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:08.366493Z","title":"V ardrop: Enh ancing training efﬁciency by reducing variate redundancy in periodic time series foreca sting","venue":null,"work_id":"25a0169e-5647-486e-859b-ff7d53744e07","year":2025},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.585542Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:929d75367e5ec3a30414cdd39d9aa5008376009ad9477416322d75cf3ebf697a","observation_id":"ec785877-7ea8-4425-b0f1-fbfb81c2da58","resolution":{"observed_at":"2026-08-07T13:52:08.541330Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:08.082920Z","title":"Towards localization via data embedding for tabPFN","venue":null,"work_id":"f27455e3-fef5-478a-9a9e-df9666db87a3","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.736104Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:3d4072ba78d3142ce5aafedb32fc2c42f20534d49bfd0a73a842e0624568f494","observation_id":"5b3ea65f-cb99-4c69-9acf-95aa9b871df0","resolution":{"observed_at":"2026-08-07T13:52:08.217963Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:07.799896Z","title":"Lagcnn: A fast yet effective model f or multivariate long-term time series forecasting","venue":null,"work_id":"f15235e0-5d49-4058-a8ba-367ada02474f","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:59.878317Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:1951ca4c15a1e02d85ee4f0b701ec7a73cbd00af2fff013b8224f0b4993fce1f","observation_id":"b9d9363f-12fd-4ebe-a03d-1079f1246503","resolution":{"observed_at":"2026-08-07T13:52:07.950717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:07.510041Z","title":"Revisiting lo ng-term time series forecasting: An investigation on afﬁne mapping, 2024","venue":null,"work_id":"ccc5c6d7-1dd6-4aac-9d0e-9697ac2013c0","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.048319Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:1675a96d22a5b5c989c617c076216c97187fb241d62328b85375c0895c896666","observation_id":"fcc77bdb-c223-4bee-a88b-b5875d205de4","resolution":{"observed_at":"2026-08-07T13:52:07.672151Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:07.188925Z","title":"Multivariate time series anomaly detection and interpretation using hie rarchical inter-metric and temporal embedding","venue":null,"work_id":"287817a4-7239-4beb-a3e4-641ff4ebad84","year":2021},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.163052Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:4ab3c9df5689d5a8e8630e717b68f9d1b59f459c02cdc43f77320e1e00074c20","observation_id":"b8b8b0f2-c778-461a-9fb8-d6388815ad16","resolution":{"observed_at":"2026-08-07T13:52:07.361452Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02332","last_updated":"2024-06-17T09:59:43Z","snapshot_observed_at":"2026-08-13T19:56:07.905624Z","submitted_at":"2024-02-04T03:54:31Z","title":"Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02332","snapshot_observed_at":"2026-08-07T13:52:00.274072Z","title":"Minus- former: Improving time series forecasting by progressivel y learning residuals","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.274072Z"},"links":{"cited_paper":"/paper/2402.02332","citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:974261efc1558c37f19eb731f8f62b8f77cdb4ea9e3c7c119b5c08e75ea930b2","observation_id":"ae963f53-3367-4376-9251-136ba6b2ccfc","resolution":{"observed_at":"2026-08-07T13:52:00.274072Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06625","last_updated":"2024-03-14T11:45:57Z","snapshot_observed_at":"2026-08-14T20:15:49.960714Z","submitted_at":"2023-10-10T13:44:09Z","title":"iTransformer: Inverted Transformers Are Effective for Time Series Forecasting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06625","snapshot_observed_at":"2026-08-07T13:52:00.354715Z","title":"itransformer: Inverted transformers are effective f or time series forecasting","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.354715Z"},"links":{"cited_paper":"/paper/2310.06625","citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:c6fc36d46e65071bea1e27af95ee5e6f3550ae1c2c0637ac9ee93c0958db4198","observation_id":"5b44136e-2772-47e0-a54a-6c603b13d4a0","resolution":{"observed_at":"2026-08-07T13:52:00.354715Z","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":"2026-08-07T13:52:06.871002Z","title":"Times2d: Multi-period de- composition and derivative mapping for general time series forecasting","venue":null,"work_id":"93afdef3-fa3b-49eb-8ed8-91a7cabd72fb","year":2025},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.441032Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:b9868711ff4c2c0b9ce73a5d3b2cf7cbb83b30e0c8ffee97175cabbfccbd393a","observation_id":"66cfb6e5-2d99-4950-a040-0fc6568fda94","resolution":{"observed_at":"2026-08-07T13:52:07.017201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:06.529839Z","title":"A time series is worth 64 words: Long-term forecasting with transformers","venue":null,"work_id":"7139349f-283b-4a39-a0b5-77a09a534e14","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.545681Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:a0208e228b2a6d25f5b463462dbd0e7bd9a5193403852ba4f611c20b6dfa9e61","observation_id":"dccc9028-1b8b-47cf-aefa-ffe61c776794","resolution":{"observed_at":"2026-08-07T13:52:06.692807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:06.269747Z","title":"Ppdformer: Channel-speci ﬁc periodic patch division for time series forecasting","venue":null,"work_id":"18a91155-3379-4cb0-899e-c419f796b762","year":2025},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.605278Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:f0a8ed41d4ae759b937d40415dad7565b6f4872789a467db79b6488a613b745e","observation_id":"9fb4d564-3253-4359-b299-c62dd00c19d0","resolution":{"observed_at":"2026-08-07T13:52:06.357783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:06.094420Z","title":"MICN: Multi-scale local and global context modeling for long-term series forecasting","venue":null,"work_id":"6463f5dd-e55f-42ca-9f36-87c8561e280b","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.711174Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:e02e983a78a9c10e5424d7a2c0a724ec54acd6ec582bf00a3fac536ae9396692","observation_id":"ca3242d1-2868-4f00-a433-999612177e8b","resolution":{"observed_at":"2026-08-07T13:52:06.151285Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.924971Z","title":"Zhang, and JUN ZHOU","venue":null,"work_id":"d66a96ee-fdb4-498b-bf62-f75a20cc2b85","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.805300Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:9286707b1bfa0ffb6db14466b6e96259e8546faa9e7dd80368b16685162570b3","observation_id":"f0e69f8f-aab4-43cf-a5ce-f55ec30a724e","resolution":{"observed_at":"2026-08-07T13:52:05.988319Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.790333Z","title":"Timexer: Empowering transformers for time series forecasting with exogenous variables","venue":null,"work_id":"c40271ed-0b95-4330-a2de-cb63d43746d2","year":2024},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:00.917070Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:dd2051c34a7e35b4e9825d82db8e04d03aa903ecb60f8c979c1543a4a4617047","observation_id":"d26af807-1026-4b7c-86bf-3d6abc88a47f","resolution":{"observed_at":"2026-08-07T13:52:05.849237Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.658147Z","title":"ETSformer: Ex- ponential smoothing transformers for time-series forecas ting, 2023","venue":null,"work_id":"5dcdef5e-9f2a-40c6-ab6f-610ff21c5f06","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.011332Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:8c1d073722617e02fcb365f118868fa5c46d8d3ee0ea79559704e4ebeecde8e7","observation_id":"e19fbf2f-eb06-4f9d-8069-2dad3279d596","resolution":{"observed_at":"2026-08-07T13:52:05.704005Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.620764Z","title":"Lino: Advancing recursive residual decomposition of linea r and nonlinear patterns for robust time series forecasting, 2025","venue":null,"work_id":"55c59980-d24c-434e-994a-c1f206a22e39","year":2025},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.138717Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:681e8f2eaaa34589de52964f6a5f48d333c8e928274be791541bac8acccc83d3","observation_id":"c80bd895-743a-41b4-aa78-8bc40cd8f3d2","resolution":{"observed_at":"2026-08-07T13:52:05.634711Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.582444Z","title":"Crossformer: Transformer utilizing cross-dimension depen- dency for multivariate time series forecasting","venue":null,"work_id":"d0b3c002-a289-48c7-ae9c-f9eda42d50e4","year":2023},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.291468Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:a316d9646113cd58c2ef0fcdf88991ea92e0adebcc375092d5be569f6de2e2ef","observation_id":"834b0094-eb14-4319-8864-70b040ce6928","resolution":{"observed_at":"2026-08-07T13:52:05.601194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.531599Z","title":null,"venue":null,"work_id":"ec09c1dd-f8da-4f63-95bc-32c8010755ba","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.410924Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:0a8670dbc71f8ff66f515429b70f7510720705def1b26dd63ee50733d4a76439","observation_id":"fbd06ee8-6647-43ed-9899-fead2dfb3d83","resolution":{"observed_at":"2026-08-07T13:52:05.575858Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.340901Z","title":null,"venue":null,"work_id":"eb4a8934-4ae9-4c3c-a7ff-22b9bfa4ea8f","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.517486Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:e699d83bb81bc5fde183c9b3fe6ab4a74581bfd27354d2bb471cede66b8501a6","observation_id":"859d0716-67b2-4a94-9f66-d6b79dbbc276","resolution":{"observed_at":"2026-08-07T13:52:05.421036Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.178367Z","title":null,"venue":null,"work_id":"94027895-b6f6-4a57-a3fe-f0dc91d2d415","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.610709Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:1ae4b9bc9398442a35359ec38ec82a4c91ca623387a05445a34630e777fb8553","observation_id":"ef8f1900-82b1-4efc-bf41-1b94f983717f","resolution":{"observed_at":"2026-08-07T13:52:05.252989Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:05.006647Z","title":null,"venue":null,"work_id":"1b81a036-87ea-40fd-8b15-45a047f3050f","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.715473Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:48d749ce3dca41548bd3b07643c940a0fb729819ceb01ccbb08e11bff59bf4d4","observation_id":"5660712d-00ef-43a1-b50e-9d0d0a396c44","resolution":{"observed_at":"2026-08-07T13:52:05.087150Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.809692Z","title":null,"venue":null,"work_id":"c63b5ada-aee1-44b1-8e63-e7f5b14b3ecd","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.808076Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:a7732a0fa64d89963a42107c9567772375d35929525f481c37691f9ec6539d1f","observation_id":"d72384c7-0e37-4ae2-bb3c-cc6240ad148c","resolution":{"observed_at":"2026-08-07T13:52:04.891314Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.676777Z","title":"The full implementation is provided in the sup plementary material and the anonymous GitHub repository","venue":null,"work_id":"5c5efe55-f3fd-4f70-a4a7-9b1970cccd4d","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.914667Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:f8a85bfda7baca66c8e328c63753e72ec5f89e8dfa8ce5ed69a083f91710d384","observation_id":"d421537a-c899-45dd-8770-e963fda4cbbf","resolution":{"observed_at":"2026-08-07T13:52:04.734443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.533045Z","title":null,"venue":null,"work_id":"7adcb388-8b2d-4e1b-83ac-73a616b89dfc","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:01.996177Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:ed1b3229cd422ce33479717b49bbfdb0b52d3fe33c82fda4de726722671ee2df","observation_id":"3bb3be47-2c37-4070-9708-ddee44295a9e","resolution":{"observed_at":"2026-08-07T13:52:04.613533Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.394418Z","title":null,"venue":null,"work_id":"a185e374-2bd1-4a6b-a6da-e73eb6bb221c","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.109711Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:0b0eab410d7a205019993e606ecaa47c57b5c16c378a154bef5674da2e2ebdb2","observation_id":"9890d1ac-c582-4dd6-8570-a6a3f33dbb44","resolution":{"observed_at":"2026-08-07T13:52:04.454610Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.250888Z","title":null,"venue":null,"work_id":"d73868ec-cce1-4817-b937-53db93f90e3d","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.168027Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:d6443e559e9bb5376932e19fabfb6f135f256f7cf24023a73ab53391ad51dfed","observation_id":"1b93cf91-efa2-47c4-975b-f8113a13fe5a","resolution":{"observed_at":"2026-08-07T13:52:04.310482Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:04.046001Z","title":null,"venue":null,"work_id":"669c7f0b-cfbe-48df-86c0-20cee773a199","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.256032Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:9bea7ab2dfe4d0dcd36ccc23a6d97f904208233c25b56dc72f34effcb84e292c","observation_id":"dfb2028f-fbbe-47ff-902e-530e1bccd0df","resolution":{"observed_at":"2026-08-07T13:52:04.149186Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:03.878711Z","title":null,"venue":null,"work_id":"3179d711-0336-4fbb-8390-a3df0b7344e9","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.370723Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:7537b3d1d827fb84acea8c6cf928a5799d7807756c03ff61fb088509a04ca585","observation_id":"feb9c28b-b958-406e-8d46-6f517a4b4fd9","resolution":{"observed_at":"2026-08-07T13:52:03.963106Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:03.703046Z","title":null,"venue":null,"work_id":"7da6f6ae-f941-48e5-a897-e32476498824","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.430628Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:5b203fb6c79ad36ccde8cde08e0f080a88e947c9b9751dad3bd82816879adb63","observation_id":"d2c65d50-ca5c-4985-8aea-5f2f7347bf96","resolution":{"observed_at":"2026-08-07T13:52:03.791004Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:03.520425Z","title":null,"venue":null,"work_id":"c1469492-e2a2-4b7c-b0a7-cebdee4c19f3","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.544734Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:c1f01f35ba6912205fcf823eb2a525cc4510742ff9fa5457fbae53a6e7a183f2","observation_id":"e00442d1-a01a-4497-bf1b-d5b11d241009","resolution":{"observed_at":"2026-08-07T13:52:03.610360Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:03.297061Z","title":null,"venue":null,"work_id":"d49ac388-3ef8-42b2-a867-3f96d881458d","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.614225Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:eb4d073540aaf2934962a8e225d6910d819f0a06ad53cf57a734781972c1ac89","observation_id":"fcbbf747-8425-475e-947a-bba4c5ae6c21","resolution":{"observed_at":"2026-08-07T13:52:03.410828Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:03.105363Z","title":null,"venue":null,"work_id":"d6da9e37-78fe-4414-857d-f4bfb6fa7bd4","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.715084Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:c2e27874402bbada2159b4d2f926d27c1e5525d102668e6196de802dd42af2a2","observation_id":"1254537d-690d-41d4-be4a-4d97be18c108","resolution":{"observed_at":"2026-08-07T13:52:03.200699Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-07T13:52:02.907550Z","title":null,"venue":null,"work_id":"13a68aa0-9d95-474c-84b7-d7a952a55cc1","year":null},"citing_paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T13:52:02.770061Z"},"links":{"citing_paper":"/paper/2505.20716"},"observation_digest":"sha256:9fa424181fc6bf21f96818621900690ea865e6f97f0595eb22ffc791b6d0bb0a","observation_id":"4c3ba215-6437-4987-874d-6c84dd3ca411","resolution":{"observed_at":"2026-08-07T13:52:03.001876Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.20716","last_updated":"2025-05-27T04:51:34Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-07T13:45:50.637523Z","submitted_at":"2025-05-27T04:51:34Z","title":"Are Data Embeddings effective in time series forecasting?"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":22},"total_outbound_references":39},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:2505.20716."}