{"as_of":"2026-08-05T01:14:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ba28938debe6c0ac03ebae1081354875df7ba1a01d4b477a1b68bfa4f359e44e","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":12,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":12,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":12,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":12,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T06:03:32.200888Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-07-03T17:38:43.405877Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2509.15105","last_updated":"2026-05-22T12:07:12Z","snapshot_observed_at":"2026-08-04T04:40:44.681486Z","submitted_at":"2025-09-18T16:11:31Z","title":"Super-Linear: A Lightweight Pretrained Mixture of Linear Experts for Time Series Forecasting","version":3},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-05-25T08:22:24.238459Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2509.15105"},"observation_digest":"sha256:2438ba181f29fedf6163b4bce89d378abf8677d48c3f1c47599ca3c25e734ce7","observation_id":"5e4b55a5-438b-43ca-822d-c83a3ef569b1","resolution":{"observed_at":"2026-05-25T08:25:34.172797Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2509.25826","last_updated":"2026-05-14T13:13:15Z","snapshot_observed_at":"2026-08-02T14:18:06.143596Z","submitted_at":"2025-09-30T06:02:26Z","title":"Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-18T13:21:02.738561Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2509.25826"},"observation_digest":"sha256:f8cf735b3003ff1538ac0debabb8639d97812d9c278cc402ac2585b40dfd227c","observation_id":"cb87921e-ce4a-4433-a67c-dba2410ea9a9","resolution":{"observed_at":"2026-05-18T13:21:23.760649Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2509.25914","last_updated":"2026-05-14T06:25:26Z","snapshot_observed_at":"2026-08-04T06:16:10.775788Z","submitted_at":"2025-09-30T08:05:59Z","title":"ReNF: Rethinking the Design of Neural Long-Term Time Series Forecasters","version":6},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-18T13:03:25.032299Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2509.25914"},"observation_digest":"sha256:940be77eec67bece18df030867a38b3819c8a2cade016d34855fb99f75da86e3","observation_id":"858cb8c7-222c-4ce7-8cc5-8c5471af6437","resolution":{"observed_at":"2026-05-18T13:06:23.959939Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-08-04T06:03:32.200888Z","title":"arXiv preprint arXiv:2410.04803 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.18662","last_updated":"2026-08-01T12:13:31Z","snapshot_observed_at":"2026-08-05T00:24:53.161665Z","submitted_at":"2026-02-20T23:47:55Z","title":"Large Causal Models for Temporal Causal Discovery","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-04T06:03:32.200888Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2602.18662"},"observation_digest":"sha256:9b5312e55efc4c77a4fbf9f9d5d9c75f839768f5cda5c35d3db42aa3a179d2ae","observation_id":"b6b7f053-90d5-4b9e-8cbb-cc1e305dca1e","resolution":{"observed_at":"2026-08-04T06:03:32.200888Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2603.04791","last_updated":"2026-04-09T08:07:11Z","snapshot_observed_at":"2026-08-02T15:01:47.892207Z","submitted_at":"2026-03-05T04:13:57Z","title":"Timer-S1: A Billion-Scale Time Series Foundation Model with Serial Scaling","version":3},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-15T16:49:19.112440Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2603.04791"},"observation_digest":"sha256:3d13aaab3b81483bf892c1e110773a2282a42306681ed54a4da7e5631765d314","observation_id":"636fe0a1-4790-4d8e-b461-c24d7070e04e","resolution":{"observed_at":"2026-05-15T16:50:10.960836Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2604.02711","last_updated":"2026-04-08T23:13:03Z","snapshot_observed_at":"2026-08-04T09:42:48.573822Z","submitted_at":"2026-04-03T04:09:47Z","title":"Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-13T18:48:40.813486Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2604.02711"},"observation_digest":"sha256:f684e82892a99ff7520b06c8827c0ad6eb86868d7392db66520f9bb4f3a81515","observation_id":"fb912135-6b0f-4314-9d63-76afb0a06ad0","resolution":{"observed_at":"2026-05-13T18:53:08.544979Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2604.14991","last_updated":"2026-04-16T13:19:55Z","snapshot_observed_at":"2026-07-06T23:02:40.364114Z","submitted_at":"2026-04-16T13:19:55Z","title":"Predicting Power-System Dynamic Trajectories with Foundation Models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-10T10:38:07.167380Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2604.14991"},"observation_digest":"sha256:3eb0637066ec73d3f021331e97b01d827e51deb702896fe1babbbe7e85b2ecbb","observation_id":"78e72ab2-f3c4-4da1-94bc-31fc7a519817","resolution":{"observed_at":"2026-05-10T10:39:37.927264Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2604.18058","last_updated":"2026-05-01T19:19:41Z","snapshot_observed_at":"2026-07-06T23:04:59.629739Z","submitted_at":"2026-04-20T10:26:54Z","title":"Sonata: A Hybrid World Model for Inertial Kinematics under Clinical Data Scarcity","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-10T04:36:51.588539Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2604.18058"},"observation_digest":"sha256:a0bddcbbffbff44356eef2b44fd419ce9021f2d0bdc05778c20dce366af960bb","observation_id":"aabf6ca6-ea7b-4940-829d-324e88a0b77b","resolution":{"observed_at":"2026-05-10T12:10:23.269283Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2605.21975","last_updated":"2026-05-21T04:09:16Z","snapshot_observed_at":"2026-07-06T23:32:20.708664Z","submitted_at":"2026-05-21T04:09:16Z","title":"Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-22T07:15:45.332957Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2605.21975"},"observation_digest":"sha256:e482d05a70ff032ac9878db09411209614201d148558998b333c1034c20d5e8f","observation_id":"e631afa3-3f28-49ff-9799-c9a63f6855a8","resolution":{"observed_at":"2026-05-22T07:16:12.891694Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2606.08630","last_updated":"2026-06-07T13:50:09Z","snapshot_observed_at":"2026-08-02T23:22:19.832178Z","submitted_at":"2026-06-07T13:50:09Z","title":"Tyan-WP: A Wind Power Foundation Model for Ultra-Short-Term Probabilistic Forecasting","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-06-27T18:52:56.379712Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2606.08630"},"observation_digest":"sha256:b8601df2b12ec6f59d0dffdb7f37318dcbe1f9bcc5213f5e955cad86e53613c0","observation_id":"1b509e6e-9705-4123-b2ed-8b51bd464837","resolution":{"observed_at":"2026-07-02T22:27:26.140236Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":"2410.04803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-07-03T17:38:43.405877Z","title":"Timer-xl: Long-context transformers for unified time series forecasting","venue":null,"work_id":"948954a0-0ae0-4fba-a694-309527a70fe7","year":2024},"citing_paper":{"arxiv_id":"2607.01918","last_updated":"2026-07-02T09:16:51Z","snapshot_observed_at":"2026-07-07T00:07:23.664493Z","submitted_at":"2026-07-02T09:16:51Z","title":"Zeus: Towards Tuning-Free Foundation Model for Time Series Analysis","version":1},"reference_index":158,"source":"arxiv_source","source_observed_at":"2026-07-03T17:34:37.552706Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2607.01918"},"observation_digest":"sha256:fbc360d5543eb9a2e9a2a27a916d867569b339a7e18f83633d6f00428414ab38","observation_id":"64c47756-e8da-436e-8539-5b7934b92be8","resolution":{"observed_at":"2026-07-03T17:38:43.407225Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.04803","snapshot_observed_at":"2026-08-03T06:43:39.045803Z","title":"Timer-xl: Long-context transformers for unified time series forecasting[J]","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.29459","last_updated":"2026-07-31T14:24:26Z","snapshot_observed_at":"2026-08-05T00:20:22.727716Z","submitted_at":"2026-07-31T14:24:26Z","title":"TFGformer: Multivariate Time Series Forecasting via Time-Frequency Graph Learning and Covariate Fusion","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-03T06:43:39.045803Z"},"links":{"cited_paper":"/paper/2410.04803","citing_paper":"/paper/2607.29459"},"observation_digest":"sha256:841acdd1d7a967b2e47c12b616b9c235b34592f9e1930999e4e4a0cf83277eaa","observation_id":"430c357e-2fec-46c6-b93b-0c91e2cbdb41","resolution":{"observed_at":"2026-08-03T06:43:39.045803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2410.04803/citation-record","integrity":"/paper/2410.04803/integrity","json":"/paper/2410.04803/citation-record.json","paper":"/paper/2410.04803"},"outbound":[],"paper":{"arxiv_id":"2410.04803","last_updated":"2025-03-02T11:22:35Z","latest_version":4,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T19:28:52.383175Z","submitted_at":"2024-10-07T07:27:39Z","title":"Timer-XL: Long-Context Transformers for Unified Time Series Forecasting"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2410.04803."}