{"as_of":"2026-08-08T13:09:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:975e026f7009e531cb4f71aa719129b077514e2d56cb1deecd546f16d4f0451b","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":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":16,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T10:32:16.549427Z","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":"2026-05-21T20:24:21.573131Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-07T10:32:16.549427Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.05019","last_updated":"2025-09-11T05:28:31Z","snapshot_observed_at":"2026-08-08T00:07:34.048389Z","submitted_at":"2025-06-05T13:27:28Z","title":"FinMultiTime: A Four-Modal Bilingual Dataset for Financial Time-Series Analysis","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T10:32:16.549427Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2506.05019"},"observation_digest":"sha256:5130da062450d7a8002ea49d648279d9c0d1acd6d4250fb6c4fd4e8c7e30345b","observation_id":"a0207199-d157-486f-8d91-43da048273aa","resolution":{"observed_at":"2026-08-07T10:32:16.549427Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2506.11512","last_updated":"2026-05-08T13:38:42Z","snapshot_observed_at":"2026-07-06T21:41:33.629441Z","submitted_at":"2025-06-13T07:13:05Z","title":"From Time Series Analysis to Question Answering: A Survey in the LLM Era","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-19T09:31:55.829045Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2506.11512"},"observation_digest":"sha256:c13b6c2390f6cde0e1cb4f61e0b78c5a4630d9c9ea8db93f3a9051f10560926e","observation_id":"a707b501-9537-462a-b70a-28645df5633b","resolution":{"observed_at":"2026-05-19T09:32:16.026303Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-07T00:57:04.612927Z","title":"arXiv preprint arXiv:2503.01875 (2025)","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.12412","last_updated":"2025-06-14T09:09:07Z","snapshot_observed_at":"2026-08-08T06:19:41.473894Z","submitted_at":"2025-06-14T09:09:07Z","title":"Cross-Domain Conditional Diffusion Models for Time Series Imputation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:57:04.612927Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2506.12412"},"observation_digest":"sha256:bfe5c7520455ca11d52a99043657dc6715644a9360df15c9b6c42148793bb13e","observation_id":"c9fd2828-a819-4a58-a84f-c9475cbd32bd","resolution":{"observed_at":"2026-08-07T00:57:04.612927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-07T00:31:46.012164Z","title":"Time-mqa: Time series multi-task question answering with context enhancement.arXiv preprint arXiv:2503.01875, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.13705","last_updated":"2025-06-16T17:12:26Z","snapshot_observed_at":"2026-08-08T00:14:13.590292Z","submitted_at":"2025-06-16T17:12:26Z","title":"TimeMaster: Training Time-Series Multimodal LLMs to Reason via Reinforcement Learning","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T00:31:46.012164Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2506.13705"},"observation_digest":"sha256:da6ce9c86dac75f8613e9745c3ee3c18e954d2666e1bf5666cadb600b9620dc3","observation_id":"caeb3e68-5a14-4c18-b675-4131a7a4b376","resolution":{"observed_at":"2026-08-07T00:31:46.012164Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2507.15066","last_updated":"2026-04-16T16:35:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-20T18:02:50Z","title":"Time-RA: Towards Time Series Reasoning for Anomaly Diagnosis with LLM Feedback","version":5},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-19T03:30:00.958369Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2507.15066"},"observation_digest":"sha256:ac6077c0e0e423aceba197f2292d9bb456c652af440a4271b71e0172c9f46215","observation_id":"ebf8bacc-03a1-4bb1-ade2-3d633ee0b3bf","resolution":{"observed_at":"2026-05-19T03:32:01.397922Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-06T13:21:26.132153Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.20762","last_updated":"2025-07-28T12:16:52Z","snapshot_observed_at":"2026-08-06T13:21:25.180625Z","submitted_at":"2025-07-28T12:16:52Z","title":"Watermarking Large Language Model-based Time Series Forecasting","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T13:21:26.132153Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2507.20762"},"observation_digest":"sha256:0fadb8706264ede1017db8311a0f7691cea2c59c59b8557978e0fb9bee3454fb","observation_id":"9223184f-e8c1-4568-bfc7-5da4e5208046","resolution":{"observed_at":"2026-08-06T13:21:26.132153Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2510.06063","last_updated":"2026-05-27T22:16:59Z","snapshot_observed_at":"2026-08-04T11:15:40.604166Z","submitted_at":"2025-10-07T15:54:34Z","title":"TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-21T20:23:40.207908Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2510.06063"},"observation_digest":"sha256:eebbffb979c2d27c36086d6be96eab1f0066ec6686ff92d68eca77a676151392","observation_id":"d34ed938-46b8-4b9a-9a41-a7407bbe973f","resolution":{"observed_at":"2026-05-21T20:24:21.574909Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-04T11:15:43.825583Z","title":"Time-mqa: Time series multi-task question answering with context enhancement, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2510.06063","last_updated":"2026-05-27T22:16:59Z","snapshot_observed_at":"2026-08-04T11:15:40.604166Z","submitted_at":"2025-10-07T15:54:34Z","title":"TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-04T11:15:43.825583Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2510.06063"},"observation_digest":"sha256:d34f18e93fc2affaf8bba7cc7de95f3fb0a2373b18534865fc7164a30a6e2397","observation_id":"1c5a846a-e516-4213-91e8-5e898a8073d7","resolution":{"observed_at":"2026-08-04T11:15:43.825583Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2510.07432","last_updated":"2026-04-06T21:49:20Z","snapshot_observed_at":"2026-07-06T22:32:03.314860Z","submitted_at":"2025-10-08T18:31:53Z","title":"TS-Agent: Understanding and Reasoning Over Raw Time Series via Iterative Insight Gathering","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-18T09:09:42.177940Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2510.07432"},"observation_digest":"sha256:ce85a7262e3cf35e0cf1fce5391c7ec949b3d906b8cfc1997702c3366857879c","observation_id":"2d74675f-1d94-4090-8b6c-ba3e5343cc2c","resolution":{"observed_at":"2026-05-18T09:11:09.604890Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-02T21:02:28.143063Z","title":"Time-mqa: Time series multi-task question answering with context enhancement.arXiv preprint arXiv:2503.01875, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.06638","last_updated":"2026-06-27T22:21:54Z","snapshot_observed_at":"2026-08-06T16:07:42.832225Z","submitted_at":"2026-02-25T05:23:23Z","title":"HEARTS: Benchmarking LLM Reasoning on Health Time Series","version":3},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-02T21:02:28.143063Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2603.06638"},"observation_digest":"sha256:fb8042b2a801c27e118600d7dac4a88899f95dc4e386939988b47fd1fa589853","observation_id":"0e9cca03-c4cc-4bd7-b16a-bde5ffdd601b","resolution":{"observed_at":"2026-08-02T21:02:28.143063Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2604.10291","last_updated":"2026-04-11T17:15:26Z","snapshot_observed_at":"2026-07-06T22:58:56.307161Z","submitted_at":"2026-04-11T17:15:26Z","title":"TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-10T15:25:02.732205Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2604.10291"},"observation_digest":"sha256:c353d54f97fe0f929d8fdc5cce210fbcdf96a85473a068e6f06e6810e18c48c9","observation_id":"94c47297-02cc-40c8-90d1-cefc4e1244a7","resolution":{"observed_at":"2026-05-11T10:36:04.289009Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":"2503.01875","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time-mqa: Time series multi-task question answering with context enhancement","venue":null,"work_id":"3cc97f85-110e-49b2-ad25-3e535462c7fc","year":2025},"citing_paper":{"arxiv_id":"2604.24935","last_updated":"2026-04-27T19:20:59Z","snapshot_observed_at":"2026-08-01T22:10:11.609444Z","submitted_at":"2026-04-27T19:20:59Z","title":"CAN-QA: A Question-Answering Benchmark for Reasoning over In-Vehicle CAN Traffic","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T02:26:10.842074Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2604.24935"},"observation_digest":"sha256:472d6a477343e0d0c718aa5f756b36ba03014d7f401b5b5227bb7debac5e732f","observation_id":"c2c49a47-7fb4-4049-aace-041039c59ec3","resolution":{"observed_at":"2026-05-11T22:46:13.197396Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-07-13T05:38:27.357469Z","title":"Time-mqa: Time series multi-task question answering with context enhancement.arXiv preprint arXiv:2503.01875, 2025a","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.08940","last_updated":"2026-07-18T17:05:31Z","snapshot_observed_at":"2026-08-07T04:58:42.085463Z","submitted_at":"2026-07-09T21:09:05Z","title":"TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-13T05:38:27.357469Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2607.08940"},"observation_digest":"sha256:64f63d0cb4120125f278e8cbf59e1ff3f99472c9a95adc100173fa754551eaf7","observation_id":"c99018a1-42fe-45a7-9d3a-ff058fdfea00","resolution":{"observed_at":"2026-07-13T05:38:27.357469Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-02T07:51:13.857375Z","title":"Time-mqa: Time series multi-task question answering with context enhancement.arXiv preprint arXiv:2503.01875, 2025a","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.08940","last_updated":"2026-07-18T17:05:31Z","snapshot_observed_at":"2026-08-07T04:58:42.085463Z","submitted_at":"2026-07-09T21:09:05Z","title":"TSRouter: Dynamic Modality-Model Selection for Time Series Reasoning","version":2},"reference_index":2016,"source":"pdf_text","source_observed_at":"2026-08-02T07:51:13.857375Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2607.08940"},"observation_digest":"sha256:d74c461e63b12f760d63c91bd39dd0281ece8d7a7bae511df99f9cce50cd9b03","observation_id":"55c6cffe-e696-441e-8f33-d8e1e0dc1bbc","resolution":{"observed_at":"2026-08-02T07:51:13.857375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-07-14T14:52:42.813309Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09880","last_updated":"2026-07-10T18:13:54Z","snapshot_observed_at":"2026-08-07T01:44:45.682937Z","submitted_at":"2026-07-10T18:13:54Z","title":"CLIR-Bench: Benchmarking Multimodal Question Answering over Irregular Clinical Time Series","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-14T14:52:42.813309Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2607.09880"},"observation_digest":"sha256:19ff901a63d61254b17e92cc8a0bc4bfdbf128f6c8d79006910e9f458fe97c45","observation_id":"cff4d9e6-f2ae-40f6-a06a-614ebcd63bca","resolution":{"observed_at":"2026-07-14T14:52:42.813309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01875","snapshot_observed_at":"2026-08-02T14:42:44.258314Z","title":"Time-mqa: Time series multi-task question answering with context enhancement, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.14109","last_updated":"2026-05-07T21:11:51Z","snapshot_observed_at":"2026-08-08T06:32:48.904917Z","submitted_at":"2026-05-07T21:11:51Z","title":"Simplicity Paradox: Debunking myths about prompting and datasets for LLM evaluation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-02T14:42:44.258314Z"},"links":{"cited_paper":"/paper/2503.01875","citing_paper":"/paper/2607.14109"},"observation_digest":"sha256:669b86dfd1f80a7210e5dc765a7f80316cca663a6547a3f736a450e35e16479f","observation_id":"b665a6cf-375d-462c-b5ac-a24d556037b0","resolution":{"observed_at":"2026-08-02T14:42:44.258314Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2503.01875/citation-record","integrity":"/paper/2503.01875/integrity","json":"/paper/2503.01875/citation-record.json","paper":"/paper/2503.01875"},"outbound":[],"paper":{"arxiv_id":"2503.01875","last_updated":"2025-06-28T18:42:47Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-08T00:13:14.578726Z","submitted_at":"2025-02-26T13:47:13Z","title":"Time-MQA: Time Series Multi-Task Question Answering with Context Enhancement"},"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":"2026-08-08T06:32:00.761636+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 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2503.01875."}