{"as_of":"2026-08-08T06:39:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:22944e7a74926b9dd0d357abf338ba10b85192d8180de33ca56b5c41f9028c84","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-09T04:31:40.284085Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2607.07640/citation-record","integrity":"/paper/2607.07640/integrity","json":"/paper/2607.07640/citation-record.json","paper":"/paper/2607.07640"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T04:35:57.888775Z","title":"Introduction to financial forecasting,","venue":null,"work_id":"8e860eba-c58b-458c-a08b-ef979bc3f913","year":1996},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:56d4d4334db9498cef91a5739f262f1567f00d6185cacbdb1152cab116b54c9a","observation_id":"82dc9b9c-fdb8-4f74-8c4c-5b64c67b9e89","resolution":{"observed_at":"2026-07-09T04:35:57.889834Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.890379Z","title":"A closer look at memorization in deep networks,","venue":null,"work_id":"2ffe4884-d805-4425-98c4-6edcb4bba81b","year":2017},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:35b38e3c4539a909d82e913ad7ab3b096c62966d459b20bad7a9dbe75a179a29","observation_id":"b6ec6188-4022-4f74-8d96-3aafaf74d4f5","resolution":{"observed_at":"2026-07-09T04:35:57.891715Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.887078Z","title":"Changing dynamics: Time-varying autoregressive models using generalized additive modeling","venue":null,"work_id":"c9cb9c0f-8dbe-4c64-99b7-def407a63deb","year":2017},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:6e8b88f4250847e848b34f1807fb3352719d396595d0f7abf711c53412a014f7","observation_id":"36af690a-cef5-4eb3-add2-d3dd8261d0e3","resolution":{"observed_at":"2026-07-09T04:35:57.888198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.892338Z","title":"Multi-head CNN- RNN for multi time series anomaly detection: An industrial case study,","venue":null,"work_id":"fb741a26-d8ec-4df7-89dd-b10c39fdece4","year":2019},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:177a9da848848b57d2ecceb84969637f8753548aec20bea2e0605c1c68831052","observation_id":"d581f7da-fa76-4da2-a5c0-32ca06bbd651","resolution":{"observed_at":"2026-07-09T04:35:57.893502Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.885270Z","title":"Recurrent neural networks for multivariate time series with missing values,","venue":null,"work_id":"9fa1c6b3-5929-4078-937d-039684e1ab70","year":2018},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:d8b7c317bb1212faeaa122f75ddb54265594ddf1209b32caf15a36e670dfbca9","observation_id":"8959aca5-0614-4f5e-875c-264828b831be","resolution":{"observed_at":"2026-07-09T04:35:57.886539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.879969Z","title":"STL: A seasonal-trend decomposition procedure based on loess,","venue":null,"work_id":"396a9255-0bac-4c45-bbc3-0992e181eaca","year":1990},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:f33e24b444fc769ae483a8e5ef69df9c9bf6bd1c7ed658372afba94ddfed106c","observation_id":"e646119b-45e3-4c42-84d4-1497ce66a4e9","resolution":{"observed_at":"2026-07-09T04:35:57.881131Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.883414Z","title":"Predicting the future by retrieving the past,","venue":null,"work_id":"98afaf44-5c53-4bb2-9a2d-a4c3c2c74b5d","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:e16b2a3329bb3bf5257c871e8a4b8a5e601d1b2e474136f16a599ccec0e4693b","observation_id":"df0ad72b-74f3-412b-a8b9-74b0820c9856","resolution":{"observed_at":"2026-07-09T04:35:57.884552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.881681Z","title":"SAITS: Self-attention-based imputation for time series,","venue":null,"work_id":"e2127902-8126-4414-9df9-dfa9b1a3784c","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:76e4e7b1f23bde750f06918955e77b1286975f65fae0c1266f041b260a47cdf6","observation_id":"74ea599a-2b03-455d-a28a-c29d268ed958","resolution":{"observed_at":"2026-07-09T04:35:57.882827Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.894039Z","title":"UCI machine learning repository,","venue":null,"work_id":"b9e22784-4124-4b01-9894-d71079364f6f","year":2017},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:5a0ccb14c1c345c2a70e56e157c25d46bf8342eb2675bef650c10524773a59d5","observation_id":"646c4c01-1d80-46cb-a1bf-862a83c6ff73","resolution":{"observed_at":"2026-07-09T04:35:57.895044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":"2312.10997","doi":"10.1186/1476-072x-8-72","metadata_source":"pith","pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","venue":"cs.CL","work_id":"b80d2790-6cd9-4c87-b3c4-de404f99a80e","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:2ae53c7fb160b8f6ab8af98976c589aef5dbf824ff2f445f01bbd7a5e682eba9","observation_id":"ffdb3d80-5318-4903-80e6-407dc9ce9874","resolution":{"observed_at":"2026-07-09T04:35:57.522479Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.895567Z","title":"Missing value imputation for multi-view urban statistical data via spatial correlation learning,","venue":null,"work_id":"a9cf6131-7f82-4d1a-a159-0b1cb0ec7c45","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:330ccfcac67a941df78e0c10cbff06afa5bad45b74b9d2449f6d0c2d5e3bf40f","observation_id":"c328d315-41ab-4c2f-b658-e42859c348ce","resolution":{"observed_at":"2026-07-09T04:35:57.896768Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.872652Z","title":"Retrieval-augmented time series forecasting,","venue":null,"work_id":"1762d8c4-7920-412c-8a40-715c90a42e23","year":2025},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:d2ad32e97f84891f53fb090bdef083bcf5f022412965784dcff6f2360915ddd2","observation_id":"8140c2bb-412d-473e-9526-1b23561867aa","resolution":{"observed_at":"2026-07-09T04:35:57.873820Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.874432Z","title":"Reversible instance normalization for accurate time series forecasting against distribution shift,","venue":null,"work_id":"f23940b6-c0f8-4289-8847-58cd87004dcc","year":2022},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:ccc0a6cb1a8e3d8a4a3ea035fef54f374e71ac8cfee5ab9dd74a2f90a196018c","observation_id":"95297865-6f75-45a6-976d-90147bf52fa0","resolution":{"observed_at":"2026-07-09T04:35:57.875628Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.866110Z","title":"Retrieval-augmented generation for knowledge-intensive NLP tasks,","venue":null,"work_id":"45171708-f2f4-4b25-b630-be8842411653","year":2020},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:6f660fd00f70afebdb2c25bc95703d866919d1c3db942825a1aaca31c29a6335","observation_id":"36ba4ba7-963a-4578-9854-0837c57a385b","resolution":{"observed_at":"2026-07-09T04:35:57.867248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2305.10721","doi":null,"metadata_source":"pith","pith_arxiv_id":"2305.10721","snapshot_observed_at":"2026-07-09T04:35:57.524329Z","title":"Revisiting Long-term Time Series Forecasting: An Investigation on Linear Mapping","venue":"cs.LG","work_id":"e9a97693-feab-4c65-a4c9-1238818c049a","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"cited_paper":"/paper/2305.10721","citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:0d32b348bf0edd6679b83579e126abf778ef5de9ed16a52de0f322c43334d293","observation_id":"ae583d47-a75f-4cf2-bd90-68f135f90748","resolution":{"observed_at":"2026-07-09T04:35:57.526331Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.867808Z","title":"Retrieval-augmented diffusion models for time series forecasting,","venue":null,"work_id":"cf2198df-fcaa-4dca-a0e8-b8f73fe2310d","year":2024},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:b4af969798ebc9eb1d32c4362998282c6ec9f0b546cc45fee4011d0491943ad4","observation_id":"87a38443-2a2f-455b-bde8-4569b8f75e5b","resolution":{"observed_at":"2026-07-09T04:35:57.872044Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.876198Z","title":"Non-stationary transformers: Exploring the stationarity in time series forecasting,","venue":null,"work_id":"65d21184-ebe9-448c-b5ab-620e6f7b384c","year":2022},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:1f9a8b130a87b8c3694e1de91939704b07c839c448acb08e534e16dcb296caf9","observation_id":"3fcfb995-9fd7-4fc9-a7f7-c9d0b7035734","resolution":{"observed_at":"2026-07-09T04:35:57.877530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.878094Z","title":"ModernTCN: A modern pure convolution structure for general time series analysis,","venue":null,"work_id":"09ac5403-9d38-4fa0-95be-853ac7033dfc","year":2024},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:2bf84e2253db3d3e07f46bc90255a4e0feaae0ca9933d40042be247a4ed0e4ba","observation_id":"7dc4be2b-3cf7-4280-bd45-3e79e718a4f5","resolution":{"observed_at":"2026-07-09T04:35:57.879402Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2602.01588","last_updated":"2026-06-26T12:41:08Z","snapshot_observed_at":"2026-08-03T05:41:24.325355Z","submitted_at":"2026-02-02T03:28:21Z","title":"Spectral Text Fusion: A Frequency-Aware Approach to Multimodal Time-Series Forecasting","version":3},"cited_work":{"arxiv_id":"2602.01588","doi":null,"metadata_source":"pith","pith_arxiv_id":"2602.01588","snapshot_observed_at":"2026-07-09T04:35:57.528132Z","title":"arXiv preprint arXiv:2602.01588 , year=","venue":"cs.LG","work_id":"fd2b088c-5ce9-4ab4-8770-7b05194c8bd5","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"cited_paper":"/paper/2602.01588","citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:2db5509a66afa8d69e3dbaced015f929a8a6264d557ae1f4512e8cf9694d828f","observation_id":"7de73e1f-6ccd-450e-a31e-342d4f5473b6","resolution":{"observed_at":"2026-07-09T04:35:57.530299Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.897344Z","title":"V ARDiff: Vision- augmented retrieval-guided diffusion for stock forecasting,","venue":null,"work_id":"cf84ae69-1261-4923-8780-b1f4eaafa6d0","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:20728657166be0da21a6a7e4cd0facdf4ca2843adc6272971906c458f76145fb","observation_id":"50b2c535-b63d-467f-bf75-74b66416a02a","resolution":{"observed_at":"2026-07-09T04:35:57.898486Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T08:16:06.846361Z","title":"A time series is worth 64 words: Long-term forecasting with transformers,","venue":null,"work_id":"122773b5-8808-4e72-bf89-c233d093434d","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:309080c9981f1adf923fde46207f9f8448a9c67bc2ab8b9cc0037d3e0e6b645f","observation_id":"91157ae3-5cec-41e4-96f7-89477c7d050a","resolution":{"observed_at":"2026-07-09T04:35:57.863819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.864392Z","title":"TimesNet: Temporal 2d-variation modeling for general time series analysis,","venue":null,"work_id":"2c76bbdc-6487-4888-ba22-03a5a8d81532","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:ebe4adfdab2743ce1dc57227f8a26798246e27dc8b11c6a560d86d027961a3d2","observation_id":"11b0bdd7-16ba-4bdc-8ad6-db8a5b1f20b1","resolution":{"observed_at":"2026-07-09T04:35:57.865561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.860982Z","title":"Autoformer: Decomposition transformers with auto-correlation for long-term series forecasting,","venue":null,"work_id":"74472449-cb79-4cfd-9c1d-436e1573e609","year":2021},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:612a4f4676f1a5e9e5c7bb18f5934a7a88caeb12034aa6cbf4a553e829a4a4d2","observation_id":"32929326-bf3b-4141-a2e3-cd38ada1d6e9","resolution":{"observed_at":"2026-07-09T04:35:57.862159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.857455Z","title":"Out-of-distribution generalization in time series: A survey,","venue":null,"work_id":"96215f09-6615-457f-bf2a-52f54afcd9f7","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:bbeac3d68b74842783316ca6a6cab4f3b9af98b34746ebf832f80b6ae74a4683","observation_id":"15ca9f41-6878-4156-971a-0ca42d395177","resolution":{"observed_at":"2026-07-09T04:35:57.858700Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.859253Z","title":"Glocal information bottleneck for time series imputation,","venue":null,"work_id":"3d342ea0-5fcb-45c3-a6f4-09fd7daaa046","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:8aa656d3819fc04ca4c7992c23a285065ef8beb73d9efcf79c46797054340285","observation_id":"2eec3524-0468-4d2b-95c5-7478b7f04f03","resolution":{"observed_at":"2026-07-09T04:35:57.860420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.854060Z","title":"Are transformers effective for time series forecasting?","venue":null,"work_id":"5fbc8e15-8dab-4596-b1e5-1495d93f028f","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:faa6d344da62dd01f6a3c0e0f6f5ed4c29922d4be92767d78b2db2f57015d6ad","observation_id":"aa588d44-9c1e-4630-9d02-9726b5a3dc48","resolution":{"observed_at":"2026-07-09T04:35:57.855188Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2605.02278","last_updated":"2026-05-04T07:09:39Z","snapshot_observed_at":"2026-08-03T01:39:18.064763Z","submitted_at":"2026-05-04T07:09:39Z","title":"HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation","version":1},"cited_work":{"arxiv_id":"2605.02278","doi":null,"metadata_source":"pith","pith_arxiv_id":"2605.02278","snapshot_observed_at":"2026-07-09T04:35:57.517752Z","title":"HELIX: Hybrid Encoding with Learnable Identity and Cross-dimensional Synthesis for Time Series Imputation","venue":"cs.LG","work_id":"0da19ed1-ea51-4206-8769-6427898325be","year":2026},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"cited_paper":"/paper/2605.02278","citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:cb564ba1fa57532343f7709cf20dc3257cb79c2541e91820613a792f540f8b5e","observation_id":"e8365fad-eb62-425e-92d5-ab44de2cae0a","resolution":{"observed_at":"2026-07-09T04:35:57.519174Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.855731Z","title":"Crossformer: Transformer utilizing cross-dimension dependency for multivariate time series forecasting,","venue":null,"work_id":"792a0683-c9e0-4795-99c3-ace2693ace02","year":2023},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:78ffbcd912f9bdeac8be2db786b34303ae70e67bdaa255536710585fae05b5ee","observation_id":"b2c3460f-45eb-4faf-a5db-2abc5e59a3b8","resolution":{"observed_at":"2026-07-09T04:35:57.856907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-07-09T04:35:57.852183Z","title":"Informer: Beyond efficient transformer for long sequence time series forecasting,","venue":null,"work_id":"dafdb71d-908a-488a-be1d-aa9547e270f0","year":2021},"citing_paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-09T04:31:40.284085Z"},"links":{"citing_paper":"/paper/2607.07640"},"observation_digest":"sha256:9e4dda9fbb11077d015e68dcaaee7577c05f9daab5b3fa53a4cabc56e11d70a4","observation_id":"abc7d492-7b7d-405e-af68-5e48233bb6bd","resolution":{"observed_at":"2026-07-09T04:35:57.853334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2607.07640","last_updated":"2026-07-08T16:59:38Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-06T23:28:30.304810Z","submitted_at":"2026-07-08T16:59:38Z","title":"ALER-TI: Aligned Latent Embedding Retrieval for Time Series Imputation"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":0,"verified_exact":3,"verified_fuzzy":25},"total_outbound_references":29},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2607.07640."}