{"as_of":"2026-08-08T09:34:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:cee130f3973597ab1c7b0b06c791dad6233cbf23ccfa9e36dc88bd5d4feb07f8","coverage":[{"denominator":52,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":52,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:46:58.571644Z","state":"measured"},{"denominator":52,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":52,"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/2506.02081/citation-record","integrity":"/paper/2506.02081/integrity","json":"/paper/2506.02081/citation-record.json","paper":"/paper/2506.02081"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:47:51.489782Z","title":"Springer International Publishing, 2 edn","venue":null,"work_id":"2b4764bd-cf6d-4274-9e5a-756d7ce2af4c","year":2017},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:45:39.440542Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:76156cf881b04bc9bc97f42606aac5bbf84c94c8834c0e89f5631063b1f5623f","observation_id":"6606a641-2d11-4daf-b7e7-b3aee9853bdf","resolution":{"observed_at":"2026-08-07T11:47:51.572133Z","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":"2026-08-07T11:47:51.263493Z","title":"Transactions on Machine Learning Research (2024)","venue":null,"work_id":"2d9f75c7-ab45-47ce-91ae-550112bca465","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:21.623810Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:069f30356775da5fc8d6b4ba97f9b627db0d76e7ec0792b5860d1d448436546f","observation_id":"3075c61c-6325-447c-890d-4c8adbd54aa2","resolution":{"observed_at":"2026-08-07T11:47:51.386540Z","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":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-07T11:46:56.237788Z","title":"arXiv preprint arXiv:2005.14165 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:56.237788Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:d5a2a461a411b3494c0ed6d972f2c64d15cf79ece040eb5154cd78ce62953b9d","observation_id":"e3a8d30f-20b2-488f-bb57-27448470e156","resolution":{"observed_at":"2026-08-07T11:46:56.237788Z","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":"2026-08-07T11:47:51.090412Z","title":"CRC Press, 6th edn","venue":null,"work_id":"8c6d176c-9b39-45a9-8587-dcd36e476aeb","year":2004},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:57.909937Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:3484498a77c6d6d1569f2addd5190b627d05a0aa9bdd1bb8cf35a10c063c2d08","observation_id":"dab69c37-fdb5-461c-9b6a-36be5860d1c9","resolution":{"observed_at":"2026-08-07T11:47:51.169571Z","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":"2026-08-07T11:47:50.940762Z","title":"In: Advances in Neural Information Processing Systems 37 (2024)","venue":null,"work_id":"5cff5d89-7933-44db-b8d5-a2b1138802d6","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:57.934502Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:e9f9d7b3817b9fc08cfe7b74347ddeff429d5d455f02e72568d636d2ad994e38","observation_id":"72edefc6-915e-4aac-9d3a-16f13b2c931f","resolution":{"observed_at":"2026-08-07T11:47:51.012903Z","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":"2026-08-07T11:47:50.867189Z","title":"In: Proceedings of the 41st International Conference on Machine Learning (2024)","venue":null,"work_id":"ea534946-3307-47be-9c9e-bbd40c180376","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:57.946384Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:e77261e576f68fd360be0e03447ef5eb8fb76bc2d2319ddc0653e21c2898517d","observation_id":"56606399-7f8b-4857-9b07-f6a9963c9b54","resolution":{"observed_at":"2026-08-07T11:47:50.898605Z","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":"2026-08-07T11:47:50.762982Z","title":"IFAC Proceedings V olumes46(20), 12–17 (2013)","venue":null,"work_id":"8b541aad-8128-4ed5-a85e-84349c7808a8","year":2013},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:57.970603Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:fc8468908c69385499d8fa0c358d4ab20da126338748a70f7d1e27f632edfa60","observation_id":"18e6797f-bcf0-438c-8383-bfcebe14a034","resolution":{"observed_at":"2026-08-07T11:47:50.811592Z","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":"2026-08-07T11:47:50.669710Z","title":"The Annals of Statistics 7, 1–26 (1979)","venue":null,"work_id":"483fe3d1-f70a-484e-b64b-fd9d295a6ea7","year":1979},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.011046Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:48afa813dd2f9106b2db145f4c236c27beede7a5cf2be3b535ba5bcebe74f55a","observation_id":"9bb32149-7919-4097-a6ec-758719b18fba","resolution":{"observed_at":"2026-08-07T11:47:50.717543Z","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":"2026-08-07T11:47:50.589048Z","title":"In: Proceedings of the 40th IEEE International Conference on Data Engineering","venue":null,"work_id":"6fed4557-d401-4be7-8c3a-3502df72ee4f","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.048968Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:1ab17d935ec39041d95daa9e77d2a45ec8cf44c52471a0a348891a662c40823d","observation_id":"624516d5-378f-430c-aa6f-6b52d8537a1b","resolution":{"observed_at":"2026-08-07T11:47:50.630093Z","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":"2026-08-07T11:47:50.500257Z","title":"In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","venue":null,"work_id":"83a06e4b-0a32-40f0-8f1d-ad93df09b298","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.061302Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:2930ff35d1b3c4a4b29f51d961fae0d035ecbfd0061176896e5728e5387d0896","observation_id":"5e148ada-7fad-4657-afd2-89c60bd6012c","resolution":{"observed_at":"2026-08-07T11:47:50.551120Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:58.116715Z","title":"In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.116715Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:dfc86d3e3754f88385a55041d2bad1b98d2cfa826993d4ce245ecb4d9d2c669c","observation_id":"2460dd48-9d23-4d68-ae48-23dc9fdea6fd","resolution":{"observed_at":"2026-08-07T11:46:58.116715Z","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":"2026-08-07T11:47:50.409597Z","title":"Circulation 101(23), e215–e220 (2000)","venue":null,"work_id":"20f68414-c7ac-4196-bf29-1a1a40501347","year":2000},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.130325Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:a5e94c69dbaabe192dcecdf3e7c3132a8f34bbe295424c6fad797888df0a2eab","observation_id":"9ed46e98-621d-458d-a993-74cae5e0747a","resolution":{"observed_at":"2026-08-07T11:47:50.454034Z","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":"2026-08-07T11:47:50.311895Z","title":"In: Proceedings of the 41st International Conference on Machine Learning (2024)","venue":null,"work_id":"16bbcebe-3dc6-4484-8033-4e5b721b1bae","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.146168Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:ad269f45efec48aff2009586941202da63ad79270e346c601cd2455aed046c9e","observation_id":"9a9b1955-b6dd-46ee-8f7e-1094d145de48","resolution":{"observed_at":"2026-08-07T11:47:50.355857Z","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":"2026-08-07T11:47:50.208429Z","title":"O’Reilly Media (2019)","venue":null,"work_id":"6da31a1c-e09a-4542-98a9-7180e2c75afd","year":2019},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.156005Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:729c54169ee4ee1c4e6d1aac9c45fa05887ac1ce7eb10db9afd74f1de7cbe01d","observation_id":"2a04afca-7123-440c-86c6-dd6e2ed69980","resolution":{"observed_at":"2026-08-07T11:47:50.266727Z","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":"2002.08909","last_updated":"2020-02-10T18:40:59Z","snapshot_observed_at":"2026-08-02T17:52:27.326803Z","submitted_at":"2020-02-10T18:40:59Z","title":"REALM: Retrieval-Augmented Language Model Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08909","snapshot_observed_at":"2026-08-07T11:46:58.163265Z","title":"arXiv preprint arXiv:2002.08909 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.163265Z"},"links":{"cited_paper":"/paper/2002.08909","citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:4391027744eb26bf1a901120ec2fd6683082889bf7bf65810f6e133a402bcc54","observation_id":"31cb8984-69ee-4185-ba41-ffba8cdfc177","resolution":{"observed_at":"2026-08-07T11:46:58.163265Z","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":"2026-08-07T11:47:50.081863Z","title":"In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","venue":null,"work_id":"60dbf9f5-74dd-451b-b44e-6371ae30987d","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.171654Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:2a362d26e9b4732e072ad4f6c28d81cfdb4fb46bf0b31f7cad193ed45a403006","observation_id":"8f1d0dc7-ecb0-4d2e-a4cb-44929ee815b9","resolution":{"observed_at":"2026-08-07T11:47:50.147716Z","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":"2026-08-07T11:47:49.988524Z","title":"In: Proceedings of the 24th ACM SIGKDD international conference on knowledge discovery and data mining","venue":null,"work_id":"68719f65-62e3-4f4c-bbe3-ecc288fc3422","year":2018},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.180066Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:6af06693493ae9d4c9a3a7d29480d3e88728c25c3b83f6813b5c20cd70525ec6","observation_id":"3931dbfc-9451-45af-b84d-57fde2083e7c","resolution":{"observed_at":"2026-08-07T11:47:50.045062Z","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":"2026-08-07T11:47:49.835070Z","title":"In: Proceedings of the 28th ACM International Conference on Information and Knowledge Management","venue":null,"work_id":"dc2a02df-0b6e-42d9-a36d-67ecf703c273","year":2019},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.189163Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:e0d0f03d6f36630fda5b32286a3c2fa02ef0d979aae8fd15180011af40d0f987","observation_id":"0af68337-7d55-4dc9-ad32-479ac0153544","resolution":{"observed_at":"2026-08-07T11:47:49.916562Z","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":"2026-08-07T11:47:49.718869Z","title":null,"venue":null,"work_id":"ed34d16b-0ddf-4842-affa-503175175f48","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.201627Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:5f015a4f0970d21a6864fc86a7dcbaebcb4e78cd41ce728a528b5c533c5f8489","observation_id":"fe5bfbe8-5a01-4bcd-9073-60b8aa5a1205","resolution":{"observed_at":"2026-08-07T11:47:49.773625Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T11:47:49.597083Z","title":"Scientific Data 3(1), 1–9 (2016)","venue":null,"work_id":"b969ddc0-d89a-4ff5-a4f1-239d23e277d1","year":2016},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.213304Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:c05b69bc8ac86d5afa55b6d7a90a1dcf5670a6e992d8fc7533fab6754ee5e90a","observation_id":"82450d5f-fa11-4180-89fa-75ea74029fe3","resolution":{"observed_at":"2026-08-07T11:47:49.661365Z","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":"2026-08-07T11:47:00.791014Z","title":"In: Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks (2021)","venue":null,"work_id":"58700ba5-a772-4969-93f3-7f0a9ff0fa91","year":2021},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.225884Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:289054ae8075c1cbb227f0d89390abd844a680caaac67545fd15866a552a4593","observation_id":"a9848b53-e402-4233-959e-4e7b82615b95","resolution":{"observed_at":"2026-08-07T11:47:49.031157Z","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":"2026-08-07T11:47:00.704490Z","title":"In: Proceedings of the 14th International Conference on Machine Learning and Applications","venue":null,"work_id":"e10f0014-45c3-4496-8dc0-a22c8a2a5e44","year":2015},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.239032Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:c569c262a9cc5f8cf69dc2ac72396a90376b84cc9fa55c19cfa9af7b4b2c9a47","observation_id":"0c8ef968-3f35-42b4-a093-d495e35a2b64","resolution":{"observed_at":"2026-08-07T11:47:00.746044Z","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":"2005.11401","last_updated":"2021-04-12T15:42:18Z","snapshot_observed_at":"2026-08-07T05:44:30.677502Z","submitted_at":"2020-05-22T21:34:34Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11401","snapshot_observed_at":"2026-08-07T11:46:58.252846Z","title":"arXiv preprint arXiv:2005.11401 (2020)","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.252846Z"},"links":{"cited_paper":"/paper/2005.11401","citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:b85b801b850c7b0b4724cb1172fa6d7835712fa2e3345548a76cd5d7960668bd","observation_id":"4c5102e5-92bb-4b98-b5f2-69db74ee8d4a","resolution":{"observed_at":"2026-08-07T11:46:58.252846Z","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":"2026-08-07T11:47:00.640006Z","title":"Proceedings of the VLDB Endowment 17(12), 4229–4232 (2024)","venue":null,"work_id":"b88f8c35-e533-4ca3-99a3-881e35403886","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.267094Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:97c73f0779cbb5d0a8fb0a9d49527b761ce0cc0c0349bc779e880a2bde9f66fc","observation_id":"58be8fe7-c844-441c-87c3-d897180e9d0d","resolution":{"observed_at":"2026-08-07T11:47:00.667283Z","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":"2026-08-07T11:47:00.569259Z","title":"In: Advances in Neural Information Processing Systems 35 (2024)","venue":null,"work_id":"ebd2240d-9ca9-4683-ae92-cee38cc9169a","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.280857Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:1efa7f296397d7177c63ff8ee2feb019736033f3498786e92439c6f771b35972","observation_id":"07afc127-e578-4788-af28-4d9fe15a475e","resolution":{"observed_at":"2026-08-07T11:47:00.599588Z","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":"2026-08-07T11:47:00.459824Z","title":"In: Proceedings of the 39th AAAI Conference on Artificial Intelligence","venue":null,"work_id":"857a0647-a7b5-4110-bbcc-9e4b7b052406","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.291543Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:f5e2dc48c98ebe56307fc938616ed8264b17d5dac30eeacc6dddba06db32d11e","observation_id":"472feb6e-0ee8-4196-9ed1-a4d5e7e05645","resolution":{"observed_at":"2026-08-07T11:47:00.508388Z","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":"2026-08-07T11:47:00.379657Z","title":"IEEE Transactions on Fuzzy Systems 23(3), 688– 700 (2014)","venue":null,"work_id":"643a4bc4-6de1-4dc8-b5a2-dc013e5f3732","year":2014},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.306299Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:0e0c3a233747305dbcfb180c42b167f5b7924bcdb6dbb813fd203fad8c748be2","observation_id":"ccefff29-36b4-4517-bcc1-007a23d85f8f","resolution":{"observed_at":"2026-08-07T11:47:00.420266Z","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":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-07T11:46:58.317184Z","title":"arXiv preprint arXiv:2303.08774 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.317184Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:5259d18a837dcf1dab8900fbc62f23e15a85011bc66a24db66b1b354c55fc894","observation_id":"f8b444b0-0a75-4d29-8503-5aaa2ba51192","resolution":{"observed_at":"2026-08-07T11:46:58.317184Z","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":"2026-08-07T11:47:00.308017Z","title":"Proceedings of the VLDB Endowment 15(11), 2774–2787 (2022)","venue":null,"work_id":"994007f1-9df6-4de7-9369-bf9269f56776","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.325351Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:337bf159dc2cccd6f01b1bf30a11500d36224e8a8c0e72413c4edf722fc3bb44","observation_id":"790831b0-4a57-4c7c-9fa2-98e075fb5b83","resolution":{"observed_at":"2026-08-07T11:47:00.340512Z","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":"2026-08-07T11:47:00.220293Z","title":"In: Proceedings of the ACM SIGMOD International Conference on Management of Data","venue":null,"work_id":"49048f30-0237-4f90-87be-1966c5fc3351","year":2015},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.334081Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:862a82fe52d54cc0f083135acb28d2ec81da9d09ad533055766a126fa05e828a","observation_id":"59505b2e-df9a-4a22-be9a-88b46b987c6a","resolution":{"observed_at":"2026-08-07T11:47:00.263152Z","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":"2026-08-07T11:47:00.149744Z","title":"Proceedings of the VLDB Endowment 15(8), 1697–1711 (2022)","venue":null,"work_id":"8c3896db-2900-408f-af80-ecb20e6b58e5","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.343128Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:2074dfca9f9576184afd12774e31693b3498c66b61e9a8a9e1c3720d836c6047","observation_id":"a7794131-7b3f-4000-a40c-d9fe5fffc1b6","resolution":{"observed_at":"2026-08-07T11:47:00.181506Z","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":"2026-08-07T11:47:00.067253Z","title":"In: Proceedings of the ACM SIGMOD International Conference on Management of Data (2020)","venue":null,"work_id":"dfa4bdf1-8b5a-4889-bf17-fc6100ddcc8f","year":2020},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.352985Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:84d48e3dbb2d47c5ac4111f4b706122de756c7ea63dc962833de9058770cb774","observation_id":"32bdab39-a5c8-48d4-82db-b12f88cc47dc","resolution":{"observed_at":"2026-08-07T11:47:00.109465Z","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":"2026-08-07T11:47:00.001742Z","title":"Proceedings of the VLDB Endowment 15(9), 1779–1797 (2022)","venue":null,"work_id":"bf20d363-0c3d-4869-ad6e-718fbd8961c3","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.364567Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:d0702fd06356347e00677962e4ce292039abe9ea9ca0ce57e0fa5d910b058c0d","observation_id":"d6752a4d-e4df-4a30-bce2-7400fc2053a0","resolution":{"observed_at":"2026-08-07T11:47:00.031119Z","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":"2026-08-07T11:46:59.918304Z","title":"In: Pro- ceedings of the 13th International Conference on Learning Representations (2025)","venue":null,"work_id":"43e28507-9078-4a7f-9472-7c87ee6b4bfd","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.371601Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:4336287ddcb0d6376d201f687ad0541db373398cfbe6cb58f50f3d3ea8b900ae","observation_id":"2639a129-b5eb-40d0-8c75-024f997031fb","resolution":{"observed_at":"2026-08-07T11:46:59.961847Z","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":"2026-08-07T11:46:59.846400Z","title":"In: Proceedings of the 13th International Conference on Learning Representations (2025)","venue":null,"work_id":"3c9569bc-dd63-47af-82b2-57b1203c1aa7","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.378709Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:067eb6c3a8dbb11911b75ceb8dbffef0ebc219cbf552af0000e51fc510223a76","observation_id":"7c2494f4-ce0c-4637-8224-456ad89b502b","resolution":{"observed_at":"2026-08-07T11:46:59.879909Z","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":"2026-08-07T11:46:59.747062Z","title":"In: Proceedings of the 12th International Conference on Learning Representations (2024)","venue":null,"work_id":"d2804c5d-b35b-45d4-a490-008fc5ff3aef","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.389729Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:243f356a9c1e9dd675c6213c09dd1bb87735cddf8eb23d2b637f783ad7e9a51a","observation_id":"b892a94a-83b9-47a4-97e7-937111625f8c","resolution":{"observed_at":"2026-08-07T11:46:59.789557Z","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":"2026-08-07T11:46:59.669778Z","title":"In: Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery and data mining","venue":null,"work_id":"e710643a-61d6-427f-88a4-ef0e92fb602f","year":2019},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.397302Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:06f10e5670879479575d39fb00a06f7fa8b578b7ba176f62d47265bf1f97e80d","observation_id":"54d70487-b607-4da4-824c-e99afa2b8705","resolution":{"observed_at":"2026-08-07T11:46:59.700437Z","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":"2026-08-07T11:46:59.580327Z","title":"In: Proceedings of the 40th IEEE International Conference on Data Engineering","venue":null,"work_id":"3b21ad6a-26e3-4c58-8d12-60c4d353adcf","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.407999Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:cc35b620006c069dc4b2106cb3890fe7437f91a7c177d97420c3875cdee57563","observation_id":"925628b4-9c9d-44e8-9ae0-88d35584649a","resolution":{"observed_at":"2026-08-07T11:46:59.619655Z","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":"2026-08-07T11:46:59.419334Z","title":"In: Advances in Neural Information Processing Systems 31 (2018)","venue":null,"work_id":"08e626e3-5b35-43b2-9f1f-9a6de79f6120","year":2018},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.420560Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:9be34980195c2ec66f4801844d5673d9c764dc340ccbe267ffc39536eed254a0","observation_id":"e35777b3-8843-450d-bb9e-2927a79ca665","resolution":{"observed_at":"2026-08-07T11:46:59.451476Z","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":"2026-08-07T11:46:59.340399Z","title":"In: Advances in Neural Information Processing Systems 30 (2017)","venue":null,"work_id":"5d8a316e-a0ee-406b-be64-e0d0e1436b32","year":2017},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.431283Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:352c743bc24ea6ae6ffef1bd5788f3b02043e9d4f8d114e09583d878aa265206","observation_id":"18f67957-b82c-4408-84e9-ab756433a60e","resolution":{"observed_at":"2026-08-07T11:46:59.380413Z","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":"2026-08-07T11:46:59.263139Z","title":"In: Proceedings of the 41st International Conference on Machine Learning (2024)","venue":null,"work_id":"a7417635-a53a-4ea2-ad58-4e9110304e54","year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.440694Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:79e0114581ea80b51c202167dab8440b838aa8f6d1c1012adda69962e53691a6","observation_id":"93476f9b-c083-45d1-9f6d-dd7c4d94caa0","resolution":{"observed_at":"2026-08-07T11:46:59.294135Z","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":"2026-08-07T11:46:59.182760Z","title":"IEEE Transactions on Knowledge and Data Engineering 35(3), 2421–2429 (2021)","venue":null,"work_id":"98963644-a16d-4522-95f3-03c4517d82d1","year":2021},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.449093Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:134f81ec446901e47e60353f7215d65ebbc222ab0ede18bcbec39ddd547fbbbf","observation_id":"d86d4073-4a46-4581-9296-452d12f2a0a7","resolution":{"observed_at":"2026-08-07T11:46:59.222264Z","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":"2026-08-07T11:46:59.115045Z","title":"In: Proceedings of the 13th International Conference on Learning Representations (2025)","venue":null,"work_id":"2b6a3229-9c25-48a4-bf59-8e51b1b07546","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.459036Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:864d3a3edef0077a44fc12a8bbe2b2a1e10a59d3dc8ba8c8e9aac8fc614be446","observation_id":"e2a9e4d3-cf98-4425-a482-81de4a37f98c","resolution":{"observed_at":"2026-08-07T11:46:59.144864Z","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":"2026-08-07T11:46:59.035421Z","title":"In: Proceedings of the ACM on Web Conference","venue":null,"work_id":"a4bf1c7a-41a0-4b48-90f5-17e46483f4ec","year":2018},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.467326Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:f95f55f45b0a5a2f1b532cc0bf51cb615a2f62a04796a1365ce1eef4e310cc2f","observation_id":"0de374df-944c-4599-b982-cb4fdaf0f899","resolution":{"observed_at":"2026-08-07T11:46:59.067858Z","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":"2026-08-07T11:46:58.989295Z","title":"In: Proceedings of the 10th International Conference on Learning Representations (2022)","venue":null,"work_id":"ead54211-e26d-4739-97f3-ace87eb2f537","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.474340Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:5af9e587f8ee6f41619ee376a6217bf21e8105d24821c34e57fc7d038a2f8f5f","observation_id":"01e8fd74-3e40-428f-a891-3437f19291e4","resolution":{"observed_at":"2026-08-07T11:46:59.018524Z","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":"2026-08-07T11:46:58.920287Z","title":"In: Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining","venue":null,"work_id":"f9ac43dd-3e25-45e3-bdd4-811ba4195270","year":2002},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.480901Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:274b227d2a7fb2ba215ef5de358881677d5ebec271c06f8b78624b19b88ec566","observation_id":"b8e1567d-fe6e-4752-b5ce-00234d861f78","resolution":{"observed_at":"2026-08-07T11:46:58.951458Z","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":"2026-08-07T11:46:58.837927Z","title":"In: Proceedings of the 16th IEEE International Conference on Data Mining","venue":null,"work_id":"7d6495a0-5b59-4590-9d6a-513af7859073","year":2016},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.503487Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:1a7a138b0f29c3a546854f856b60008b59291b28ea13a2f0dbc3ec840a3dd42a","observation_id":"c1a146d8-eba5-4343-8ee3-83e108f45b56","resolution":{"observed_at":"2026-08-07T11:46:58.872152Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:46:58.519458Z","title":"ACM Computing Surveys 57(1), 1–42 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.519458Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:3c6d20c1bc894f2dcf248ca04f76a4a0bcdce55fd1c9871c306b6c3a2e79910b","observation_id":"45a4a301-31ba-4ec3-acb6-7a0f364a80e9","resolution":{"observed_at":"2026-08-07T11:46:58.519458Z","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":"2026-08-07T11:46:58.733505Z","title":"In: Advances in Neural Information Processing Systems 35 (2022)","venue":null,"work_id":"5f81d581-5734-4355-b2e8-f18c1edc5e31","year":2022},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.530218Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:5924ea1ae1c99b5bf3ef818c92827f8da97d31cef284e416c820ffd477fddf59","observation_id":"efccf8a8-8624-4f22-9cf6-d357e8a906d5","resolution":{"observed_at":"2026-08-07T11:46:58.767369Z","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":"2026-08-07T11:46:58.665992Z","title":"In: Proceedings of the 13th International Conference on Learning Representations (2025)","venue":null,"work_id":"09d04647-259d-400d-8016-8f2843d502f7","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.539200Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:113c642c1720339cb1a4a96581770b7217a74dca5b7afe16cf749a3e576f2488","observation_id":"bef4f701-eef2-4670-9ae9-5384e3e0be79","resolution":{"observed_at":"2026-08-07T11:46:58.686994Z","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":"2026-08-07T11:46:58.645629Z","title":null,"venue":null,"work_id":"7a4444dc-353b-4bda-b86e-48e85d55a0b6","year":2025},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.559049Z"},"links":{"citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:66aaa7f127b380d8c26ee1e034951ec66643d790a62a33306812080f8223bde9","observation_id":"82946ff3-95ca-4f11-9fa7-9287a5a04eea","resolution":{"observed_at":"2026-08-07T11:46:58.652732Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2411.02465","last_updated":"2024-11-04T10:28:41Z","snapshot_observed_at":"2026-08-08T05:38:17.553585Z","submitted_at":"2024-11-04T10:28:41Z","title":"See it, Think it, Sorted: Large Multimodal Models are Few-shot Time Series Anomaly Analyzers","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02465","snapshot_observed_at":"2026-08-07T11:46:58.571644Z","title":"start\": ...,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:46:58.571644Z"},"links":{"cited_paper":"/paper/2411.02465","citing_paper":"/paper/2506.02081"},"observation_digest":"sha256:9a35d6feef0ddfa92b06bff773204e0be3abb8a1104d1be460d04a05a47ed847","observation_id":"1ed83cda-cb34-48ff-a725-afb3f2fcda15","resolution":{"observed_at":"2026-08-07T11:46:58.571644Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.02081","last_updated":"2025-06-02T10:25:35Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T04:34:31.394134Z","submitted_at":"2025-06-02T10:25:35Z","title":"RATFM: Retrieval-augmented Time Series Foundation Model for Anomaly Detection"},"reference_resolution":{"displayed":52,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":8,"verified_exact":0,"verified_fuzzy":43},"total_outbound_references":52},"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 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2506.02081."}