{"as_of":"2026-08-07T12:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:76a385a027660a8851d9c282919871f49bc1a33d615fd63ecb44220cee4f9b0d","coverage":[{"denominator":57,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":57,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:04:09.057258Z","state":"measured"},{"denominator":64,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":64,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:27:17.366480Z","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":"2026-05-15T21:46:43.208349Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-08-07T04:27:17.366480Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.10630","last_updated":"2026-06-03T16:47:53Z","snapshot_observed_at":"2026-08-07T04:19:07.939332Z","submitted_at":"2025-06-12T12:15:50Z","title":"Time Series Forecasting as Reasoning: A Slow-Thinking Approach with Reinforced LLMs","version":3},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T04:27:17.366480Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2506.10630"},"observation_digest":"sha256:e64346ac742479e24b00fa95f5d7db984027e2b6ff9e5c1e92a49cddf5b61f32","observation_id":"9f5d56cd-3c43-4880-8fa3-5eebbb48e5ac","resolution":{"observed_at":"2026-08-07T04:27:17.366480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":"2506.20093","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matthew Willetts, Sven Hollowell, Louis Aslett, Chris Holmes, and Aiden Doherty","venue":null,"work_id":"af35b36b-1655-4751-b43c-1b92d66a44f5","year":2025},"citing_paper":{"arxiv_id":"2602.14200","last_updated":"2026-06-30T15:10:55Z","snapshot_observed_at":"2026-08-02T23:21:30.159893Z","submitted_at":"2026-02-15T15:50:02Z","title":"TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning","version":5},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-15T21:42:11.825510Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2602.14200"},"observation_digest":"sha256:a8e5500e4f34e9d58140cb80790cfc7c07ead596280afbd43371bc6f883523c1","observation_id":"820044b0-a0d7-4297-a403-731773203b96","resolution":{"observed_at":"2026-05-15T21:46:43.212152Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-08-02T23:21:32.958348Z","title":"Matthew Willetts, Sven Hollowell, Louis Aslett, Chris Holmes, and Aiden Doherty","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.14200","last_updated":"2026-06-30T15:10:55Z","snapshot_observed_at":"2026-08-02T23:21:30.159893Z","submitted_at":"2026-02-15T15:50:02Z","title":"TS-Haystack: A Multi-Task Retrieval Benchmark for Long-Context Time-Series Reasoning","version":6},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-02T23:21:32.958348Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2602.14200"},"observation_digest":"sha256:02a834cf56e336d11c67870d6909a0598efa4e4569353439dc2f81e439eb3b11","observation_id":"71647806-738d-43da-bbdd-549690ea3a6f","resolution":{"observed_at":"2026-08-02T23:21:32.958348Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":"2506.20093","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matthew Willetts, Sven Hollowell, Louis Aslett, Chris Holmes, and Aiden Doherty","venue":null,"work_id":"af35b36b-1655-4751-b43c-1b92d66a44f5","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":45,"source":"pdf_text","source_observed_at":"2026-05-10T15:25:02.732205Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2604.10291"},"observation_digest":"sha256:6e108219d9b1825b1ea81c1426d0d6d5fdd1d2a1a299df2cea16165b3398c497","observation_id":"6d05be31-e407-4eb1-8272-7c43143d676a","resolution":{"observed_at":"2026-05-11T10:36:04.408759Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":"2506.20093","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matthew Willetts, Sven Hollowell, Louis Aslett, Chris Holmes, and Aiden Doherty","venue":null,"work_id":"af35b36b-1655-4751-b43c-1b92d66a44f5","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":21,"source":"pdf_text","source_observed_at":"2026-05-08T02:26:10.842074Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2604.24935"},"observation_digest":"sha256:9c18aa142ed843ccc3ff60408cf42655c88a0dbe75ea71307d939da028672a7c","observation_id":"31d9bcf3-eb61-48d4-9d89-84c8ea632451","resolution":{"observed_at":"2026-05-11T22:46:13.201714Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":"2506.20093","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.20093","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Matthew Willetts, Sven Hollowell, Louis Aslett, Chris Holmes, and Aiden Doherty","venue":null,"work_id":"af35b36b-1655-4751-b43c-1b92d66a44f5","year":2025},"citing_paper":{"arxiv_id":"2605.08614","last_updated":"2026-05-09T02:17:39Z","snapshot_observed_at":"2026-08-02T11:55:00.952125Z","submitted_at":"2026-05-09T02:17:39Z","title":"DiagnosticIQ: A Benchmark for LLM-Based Industrial Maintenance Action Recommendation from Symbolic Rules","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-12T01:00:13.017290Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2605.08614"},"observation_digest":"sha256:db9158de5414019b1c8032f84eb8680ec1fd56c1819e07b95c63674b558ee486","observation_id":"d6300298-881d-4845-8d6e-b0c043445598","resolution":{"observed_at":"2026-05-12T08:31:25.929105Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.20093","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":40,"source":"pdf_text","source_observed_at":"2026-07-14T14:52:42.813309Z"},"links":{"cited_paper":"/paper/2506.20093","citing_paper":"/paper/2607.09880"},"observation_digest":"sha256:7e9ee2f1135ce8516a1e8dffdf873e4f84a5ea5fd8f67ec43e9eef18bb21f711","observation_id":"921c9e46-868e-4956-96dd-75ca8ea6e1e8","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"}}],"links":{"evidence":"/evidence","html":"/paper/2506.20093/citation-record","integrity":"/paper/2506.20093/integrity","json":"/paper/2506.20093/citation-record.json","paper":"/paper/2506.20093"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:04:08.593493Z","title":"L., and Parikh, D","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.593493Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:ea2cfdadb45e17c2b43de56aa7fea238b698152ab495de218c9bb3c93ad84e34","observation_id":"46d32590-f5cf-4398-84f0-925937e35322","resolution":{"observed_at":"2026-08-06T23:04:08.593493Z","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":"2026-08-06T23:04:10.338283Z","title":"Aircraft Engine Run-to-Failure Dataset under Real Flight Conditions for Prognostics and Diagnostics","venue":null,"work_id":"e4cbb1fd-8b95-4507-9210-e9522261a4fc","year":2021},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.603735Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:2f09702655501dc2fdcf5a97f69dc1c5cf6a2b8980b111a514d40e375b6f5189","observation_id":"7fbe2e15-7377-4338-9db2-b1909ae35e77","resolution":{"observed_at":"2026-08-06T23:04:10.343757Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.320365Z","title":"Accurate medium-range global weather forecasting with 3d neural networks","venue":null,"work_id":"49358820-ecbb-45de-bded-07ff042313b5","year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.610986Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:6e442807c641c86375b004e12a51c882de8e5c1dae4b0400f45c91b1718c9f61","observation_id":"685ae8ce-fc38-43a8-8d2e-9cdee5cd2366","resolution":{"observed_at":"2026-08-06T23:04:10.325177Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14752","last_updated":"2024-10-18T02:37:14Z","snapshot_observed_at":"2026-07-06T19:36:10.759412Z","submitted_at":"2024-10-18T02:37:14Z","title":"TimeSeriesExam: A time series understanding exam","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14752","snapshot_observed_at":"2026-08-06T23:04:08.625783Z","title":"Timeseriesexam: A time series understanding exam for large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.625783Z"},"links":{"cited_paper":"/paper/2410.14752","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:097e0b5dd94f12081f6223dbb630c908f340f3c34baea5793a3f5267c642f30b","observation_id":"cb089b2d-9228-4e33-bced-042685872e92","resolution":{"observed_at":"2026-08-06T23:04:08.625783Z","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":"2026-08-06T23:04:10.300423Z","title":null,"venue":null,"work_id":"74fbdf58-82e6-484c-8338-b723927bb9ea","year":1991},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.639772Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:17c6d1eebcc8ca496a6f735a8822bf8a0fe244e37a5bb34f3e5302fcf260f2d4","observation_id":"afe80499-c473-4f43-b199-c1bd76591e4a","resolution":{"observed_at":"2026-08-06T23:04:10.306728Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.06500","last_updated":"2023-06-15T08:00:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-05-11T00:38:10Z","title":"InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.06500","snapshot_observed_at":"2026-08-06T23:04:08.655925Z","title":"Instructblip: Towards general-purpose vision-language models with instruction tuning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.655925Z"},"links":{"cited_paper":"/paper/2305.06500","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:85433dc5774f9777c7842f941357dad8f779108a68b6f89032d4899bd1d3a8b8","observation_id":"27347cf9-9491-4943-baf7-c3dd84c6c15f","resolution":{"observed_at":"2026-08-06T23:04:08.655925Z","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":"2026-08-06T23:04:10.278755Z","title":"Z., Webb, G","venue":null,"work_id":"2608a879-b144-4a51-a241-4b4abe573b6a","year":2025},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.663911Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:0e0f0df06e18c84bb4e48c97ba21a060e81352861aa508093856056b589cfd15","observation_id":"75d20e53-1b55-4551-8e42-7499a01d75c9","resolution":{"observed_at":"2026-08-06T23:04:10.288552Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.261390Z","title":"M., Parikh, D., and Batra, D","venue":null,"work_id":"78675a3c-c4c7-494d-846b-92ae86b6a87c","year":2017},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.670809Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:a8e3d5816bb6ecdd6a8efce76b97b0a484d9a1bcbc362a14397271cfdd9efec3","observation_id":"e00a4188-2e23-42be-a40d-94fcbe539e19","resolution":{"observed_at":"2026-08-06T23:04:10.266661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.244871Z","title":null,"venue":null,"work_id":"3a2182a9-ce78-45da-8a2d-fdfc01beff63","year":2019},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.678706Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:5f697c5ae0f99bf82c26482589b811580b581ca28b6b507e87e2700b9fc6f4f5","observation_id":"8d4fae54-2517-4717-a0eb-30bd52714fc8","resolution":{"observed_at":"2026-08-06T23:04:10.249922Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.225052Z","title":"Glm: General language model pretraining with autoregressive blank infilling and task-specific fine-tuning","venue":null,"work_id":"bfc1b49e-117c-4d17-a9b6-6fb46e221f44","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.686210Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:209b892fd02aaa08cc64b1b3bcd72942a48822df94ce9fa9e89ee2ad5f30c301","observation_id":"6ab29595-d66a-49e8-a50f-d06a4d7adb50","resolution":{"observed_at":"2026-08-06T23:04:10.231518Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.204554Z","title":"Units: A unified multi-task time series model","venue":null,"work_id":"3e39efb3-4dcc-4a4b-b116-d56d07158e39","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.691412Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:03e86131eb92d25ee43c17e4e862f300ca69c0dc00c9bbec5ad470ccafa95bfe","observation_id":"85511774-9b76-4d35-90e6-ba86c3988394","resolution":{"observed_at":"2026-08-06T23:04:10.210729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:08.714856Z","title":"MOMENT : A family of open time-series foundation models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.714856Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:682e9e76855f35c9f762bbec03dfb4601e4fa1a10426902051d8e538f3c889a8","observation_id":"126f1382-b0f1-486d-b606-f13c44d330cf","resolution":{"observed_at":"2026-08-06T23:04:08.714856Z","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":"2026-08-06T23:04:10.168328Z","title":"Vector quantization pretraining for eeg time series with random projection and phase alignment","venue":null,"work_id":"ec930bb1-6d5b-4280-a975-5e06e400015e","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.747451Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:96c54303c79b1141ab059de082b695989a78a39b7042b220465ff8f8f05ca65a","observation_id":"e40355b8-54c2-4349-ad49-cfc497019ade","resolution":{"observed_at":"2026-08-06T23:04:10.174444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.148639Z","title":null,"venue":null,"work_id":"1d0ff05b-bc1e-4cf6-b5d7-6b94fdaba94b","year":2020},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.753933Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:4d4e0961a74b4b3bbf9ae7ded601b4149a0556dbab181defb1b2110ee928f35c","observation_id":"47cdc598-4795-41c8-81d0-9172bfd5c2e8","resolution":{"observed_at":"2026-08-06T23:04:10.154509Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.125590Z","title":"Y., Wen, Q., Zambon, D., Alippi, C., Webb, G","venue":null,"work_id":"df07c274-2307-4840-8c69-f5e46665fd0e","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.759702Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:e18f58951d35bcf53dae77daea34250e882ade7676cd7cc8de7c1bf431b792f6","observation_id":"bbb91670-4b8d-4755-b652-827c0ac6c952","resolution":{"observed_at":"2026-08-06T23:04:10.130646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.106729Z","title":"Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., et al","venue":null,"work_id":"f7c4d653-63cc-41cb-8471-1e6541213a8f","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.777433Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:7cc9562650e7c9f61abb749d1caed6b954cbc57c4aa63e1bb2b69fcc9748f402","observation_id":"fb4c23bf-d99e-4263-9b0a-fea91cf0c048","resolution":{"observed_at":"2026-08-06T23:04:10.112124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.088728Z","title":"Position: What can large language models tell us about time series analysis","venue":null,"work_id":"fdf9b0f6-a49e-44d4-8c73-0092bbb7f2c3","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.783822Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:b002572ea4153a8b75dd3b3ea08d406a00838d3979aeda80f8218c71e8a81c9f","observation_id":"5c723f0c-da1c-4fa3-9ce1-5de2db7a62f3","resolution":{"observed_at":"2026-08-06T23:04:10.095702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:08.795336Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.795336Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:38b38cc1c341038a533f1e3de6b2d7abe007dcc2f2dffd7b656982e6ead68150","observation_id":"05b31b23-d68e-4bef-bbde-edcc874d3635","resolution":{"observed_at":"2026-08-06T23:04:08.795336Z","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":"2026-08-06T23:04:10.057463Z","title":"Rouge: A package for automatic evaluation of summaries","venue":null,"work_id":"8dca88e7-99b9-4e31-af5e-09cf80c9c98a","year":2004},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.808677Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:28c764ac4c551e01fe33dda7a59f76eba9ec0613e6f85cafaf9a422b6e350078","observation_id":"b2c5da9d-0b6d-42da-875b-cfe032314921","resolution":{"observed_at":"2026-08-06T23:04:10.062030Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.041823Z","title":"B., Sharma, M., Cui, J., Wen, Q., Zhang, C., et al","venue":null,"work_id":"427d067b-ce33-42cf-9e10-551137c0ddea","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.814888Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:55ecd3acb800b2b286ebf0caafc0e83171bcc5795ab59be304869f7cc79e907e","observation_id":"7b83135b-a8f9-4df6-be70-e0faef0b83f7","resolution":{"observed_at":"2026-08-06T23:04:10.046513Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.024917Z","title":"itransformer: Inverted transformers are effective for time series forecasting","venue":null,"work_id":"f99052c2-1ea6-4ad7-bf85-b82dd3477fc7","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.820307Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:b1733269e7196c1436ab6001d99424131393f2b1e9ad922be03f290061921f92","observation_id":"15124c7a-efa2-4e1b-afa4-0b36bb64689b","resolution":{"observed_at":"2026-08-06T23:04:10.030204Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:10.004215Z","title":"Autotimes: Autoregressive time series forecasters via large language models","venue":null,"work_id":"ca00c162-fed2-4d03-8c3e-4bb187a947e7","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.825569Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:e1b6e6070e699b5d94b9b279539f92fbd65d1d30f93fefa83bf23f3f40b56d36","observation_id":"05fe81fa-7624-499d-aee1-ac22358426c4","resolution":{"observed_at":"2026-08-06T23:04:10.011521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.986227Z","title":"Timer : Generative pre-trained transformers are large time series models","venue":null,"work_id":"00a62d88-bfa9-4ba0-9e42-919c36d11b5c","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.830901Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:6acbe7d7b24122e8940c11c00e071477dfbdb1929b9cefc4475aa23af4efe7f8","observation_id":"f8b01855-c3c5-481f-a428-48cbb4fc1bb8","resolution":{"observed_at":"2026-08-06T23:04:09.991424Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:08.838224Z","title":"Vilbert: Pretraining task-agnostic visiolinguistic representations for vision-and-language tasks","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.838224Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:bdb96fff78e268af302a6619edb5c2a9aa1b030cc794ad1d722c5a7316c10781","observation_id":"c973a13c-ad16-47d3-8388-76eb0160e032","resolution":{"observed_at":"2026-08-06T23:04:08.838224Z","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":"2026-08-06T23:04:09.954199Z","title":"Y., Chen, B., Williamson, D","venue":null,"work_id":"0b701286-77cb-40d0-9d49-a855e376e1db","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.844502Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:0bc79a0ea3e6673610f31f1e00628fcacec749305faafe5e210c6c2bf1a2db03","observation_id":"7b428976-7b0e-4b08-8bd0-eb23bd5da745","resolution":{"observed_at":"2026-08-06T23:04:09.959838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:08.850256Z","title":"Nguyen, N., Sinthong, P., and Kalagnanam, J","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.850256Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:75080d7e32a26dc25e88908e11c8eff862a6fe5c448e35fc8f1fa4b35dc3d27b","observation_id":"8b69f8ad-2e3d-4048-9add-dd47facfcb96","resolution":{"observed_at":"2026-08-06T23:04:08.850256Z","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":"2026-08-06T23:04:09.921591Z","title":"Gpt-4 technical report, 2024","venue":null,"work_id":"7d2991f9-0120-4d3e-a2be-1e51e6ce5acf","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.855785Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:187f8236a51a1fd816769c7fb0dfe249cc33a62b7971bfc21d8d07691a5138aa","observation_id":"dd03ad20-1d07-4dd1-9be2-4846d689d19a","resolution":{"observed_at":"2026-08-06T23:04:09.928315Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.902621Z","title":"N., Carpov, D., Chapados, N., and Bengio, Y","venue":null,"work_id":"76dce447-73ba-47de-a3b2-09dd20f36e7b","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.861584Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:9d1a65d49f5aef75d76b1bbd1fde3e25692254013a76a98e78bb4e6db2b044cd","observation_id":"76432076-a22f-40b6-b021-2e75baf51276","resolution":{"observed_at":"2026-08-06T23:04:09.908153Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.884008Z","title":"Bleu: a method for automatic evaluation of machine translation","venue":null,"work_id":"6db40189-cb1c-49b5-9324-75e4b327489b","year":2002},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.868689Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:5498945e95ac592a324a0c9703c394d0d5f9422fd30a18c88d3613113623dc9b","observation_id":"d37d0f76-23de-45c6-84a6-1a76ceccc039","resolution":{"observed_at":"2026-08-06T23:04:09.889566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.05250","last_updated":"2016-10-11T02:42:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2016-06-16T16:36:00Z","title":"SQuAD: 100,000+ Questions for Machine Comprehension of Text","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.05250","snapshot_observed_at":"2026-08-06T23:04:08.874616Z","title":"Squad: 100,000+ questions for machine comprehension of text","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.874616Z"},"links":{"cited_paper":"/paper/1606.05250","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:a5e4f03408bcd8ea4300c98ec81e793a1b733eb48577f75e8542065f75bb8c0a","observation_id":"6641e5fc-044e-4912-8e7b-37a2a7c06bb0","resolution":{"observed_at":"2026-08-06T23:04:08.874616Z","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":"2026-08-06T23:04:09.866138Z","title":"M., Xing, E., Yang, M.-H., and Khan, F","venue":null,"work_id":"2a91f6a5-e442-484d-9cf8-630be5678f6b","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.880646Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:c0dd268af46dedc51cd41bf1cebdd1e409da200116510edb7744dbfbe1d7fcb5","observation_id":"e90c5df0-b08e-47b0-b785-0b377ed6ff99","resolution":{"observed_at":"2026-08-06T23:04:09.870888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1704.04368","last_updated":"2017-04-25T05:47:50Z","snapshot_observed_at":"2026-07-06T05:37:49.239583Z","submitted_at":"2017-04-14T07:55:19Z","title":"Get To The Point: Summarization with Pointer-Generator Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1704.04368","snapshot_observed_at":"2026-08-06T23:04:08.885816Z","title":"J., and Manning, C","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.885816Z"},"links":{"cited_paper":"/paper/1704.04368","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:86801a6ac75f05a700bf2e92f9ed3aedf0e5ae3377bff3a2aee2dd18535283b2","observation_id":"e3e1f65a-e9c7-43be-95c6-a427037620da","resolution":{"observed_at":"2026-08-06T23:04:08.885816Z","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":"2026-08-06T23:04:09.849695Z","title":"H., Stoffer, D","venue":null,"work_id":"b438d8b2-5162-4b7a-bee4-d9e2100109b2","year":2017},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.891367Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:516ce10f1803e15859153b1a711593dbd4de9d70591c331d5cc5e91486fc91a7","observation_id":"a2fbdaf8-8c79-4d1e-bf4f-d4385e141f46","resolution":{"observed_at":"2026-08-06T23:04:09.854778Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.827513Z","title":"Generative multimodal models are in-context learners","venue":null,"work_id":"feff308f-0dfc-49f4-9b58-55370175721f","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.897785Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:22ed264a3bc85ba05369d8c0839ba73b20735f2bdac5652a1d915fc8564903ce","observation_id":"e50ed1c9-1f03-4873-9e4f-e30747212325","resolution":{"observed_at":"2026-08-06T23:04:09.833173Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.811276Z","title":"and Bansal, M","venue":null,"work_id":"4a09f89d-70a2-49e9-aca1-ac8efd005216","year":2019},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.904014Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:ee190b2920006b56a3fdc749c10f07a5b2bb14f68c3539e3633a2cd3e06a9269","observation_id":"270d216c-47e5-4025-9e8f-4b66cc1185ed","resolution":{"observed_at":"2026-08-06T23:04:09.816191Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-06T23:04:08.909653Z","title":"M., Hauth, A., Millican, K., et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.909653Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:0ccd79b37f37c6c3ffd84af3f15f9f67e938f8868522a14401400b95ef867a47","observation_id":"b1ee0f8d-ef08-4a75-bd0a-428a14af4c87","resolution":{"observed_at":"2026-08-06T23:04:08.909653Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-06T23:04:08.917498Z","title":"Llama: Open and efficient foundation language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.917498Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:90f63990eff72429cd560b0c9500676fdf315d08e5cb22ffb1bd4f51bc6173aa","observation_id":"db41f95c-d256-4bea-b720-a29fc2ece96d","resolution":{"observed_at":"2026-08-06T23:04:08.917498Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:04:08.924820Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.924820Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:76a7710869bee966a221f416b230dfcd346274b5fc06dbf04fd403e3c51e9994","observation_id":"e726cd44-a090-422e-bda4-3e13003881bc","resolution":{"observed_at":"2026-08-06T23:04:08.924820Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.11376","last_updated":"2024-12-16T02:04:06Z","snapshot_observed_at":"2026-07-06T20:07:28.545657Z","submitted_at":"2024-12-16T02:04:06Z","title":"ChatTime: A Unified Multimodal Time Series Foundation Model Bridging Numerical and Textual Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.11376","snapshot_observed_at":"2026-08-06T23:04:08.933361Z","title":"Chattime: A unified multimodal time series foundation model bridging numerical and textual data","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.933361Z"},"links":{"cited_paper":"/paper/2412.11376","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:113a4c8f02dba1c903cb8f8c766f898abe754070d68755c378513441bdf04504","observation_id":"b0112e36-6d59-4ada-bfef-001d254e0070","resolution":{"observed_at":"2026-08-06T23:04:08.933361Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.17515","last_updated":"2024-10-30T12:04:18Z","snapshot_observed_at":"2026-08-02T16:11:46.756432Z","submitted_at":"2024-09-26T03:50:22Z","title":"From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.17515","snapshot_observed_at":"2026-08-06T23:04:08.939673Z","title":"From news to forecast: Integrating event analysis in llm-based time series forecasting with reflection","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.939673Z"},"links":{"cited_paper":"/paper/2409.17515","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:12107b16f50b74bf51ca0ed0d8ecda45e5252e47f699cd221a2aa98ef1a73f72","observation_id":"97a58448-d033-4c61-b03b-43dd3c69043b","resolution":{"observed_at":"2026-08-06T23:04:08.939673Z","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":"2026-08-06T23:04:09.777983Z","title":"Establishment of super sonic inlet flow pattern monitoring system: A workflow","venue":null,"work_id":"7d694e35-711f-4ba8-9b9d-338300c5a52d","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.946011Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:d233057e23d8b257719222f1fe8bbbd2740872ddee33b32657cb77622f815e91","observation_id":"40c287d7-7a39-43f8-b0b8-c7550a3f093d","resolution":{"observed_at":"2026-08-06T23:04:09.784312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.761069Z","title":"Self-supervised health representation decomposition based on contrast learning","venue":null,"work_id":"8b084995-f847-4622-b1f3-8fbf71f5c383","year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.953284Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:ad3e14d2ab793791562623f1e752b8e8c964bdd8b7f175cde40f8f0c5795fc6a","observation_id":"b4868ebf-451d-4e67-b473-0c58a1db0b7e","resolution":{"observed_at":"2026-08-06T23:04:09.766275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.742324Z","title":"Incorporating prior knowledge into self-supervised representation learning for long PHM signal","venue":null,"work_id":"55441fd4-37df-420e-b8d9-22d52bbb44d9","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.958958Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:4d3c3297c0c6cc677bcd85af48d8c8d46fc71ef63a9fc7e8e698b2969715982e","observation_id":"6bab9b86-aeef-4540-bd7c-ff899bd19804","resolution":{"observed_at":"2026-08-06T23:04:09.747731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:08.966858Z","title":"Leveraging large self-supervised time-series models for transferable diagnosis in cross-aircraft type bleed air system","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.966858Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:17bdeb2212faee36d244da3b61882f040a9c3fec2efb8d3b70689a510f3b6bec","observation_id":"918aeb8f-37e9-40c8-9fa7-f3d281934c69","resolution":{"observed_at":"2026-08-06T23:04:08.966858Z","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":"2026-08-06T23:04:09.724695Z","title":"Data-driven dynamic health index construction for diagnosis and prognosis of engine bleed air system","venue":null,"work_id":"7985d353-c2ed-4ca3-a5e4-a0caa924314e","year":2025},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.972832Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:ebf180d907fd15cad20c47881cd404c4256a713d0f0183f20b6d69ce8fda4faa","observation_id":"be4b2841-5ec4-4c48-909d-9a7c446d8707","resolution":{"observed_at":"2026-08-06T23:04:09.730211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.705205Z","title":"Emergent abilities of large language models","venue":null,"work_id":"4b4bb2bb-6384-4ecf-ab75-8acc37c23282","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.978458Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:94de90d02cc2d67f00cf26f47de6a7f12f702f0194337c54d023dfdd9a7e1143","observation_id":"5487bdf3-4fb5-4294-a8d0-a0f1b2cd2ed5","resolution":{"observed_at":"2026-08-06T23:04:09.710592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.684376Z","title":"Interpretable weather forecasting for worldwide stations with a unified deep model","venue":null,"work_id":"45adad48-5ad6-4371-92e0-441b6ef8257e","year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.984361Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:46d8ed5e98a07e6e80ad0e1270bc6c0625f8540ddcddd0db192f32016b299715","observation_id":"58d16cb1-0a4a-4163-bd52-570c3c2e5e69","resolution":{"observed_at":"2026-08-06T23:04:09.690651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-06T23:04:08.991539Z","title":"Qwen2.5 technical report","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.991539Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:64faec431a23a4725617b126fd57b9c891100523d4ef70535560b5f9ee5e5904","observation_id":"629dd93d-bcce-4a90-857b-af19b9f770a3","resolution":{"observed_at":"2026-08-06T23:04:08.991539Z","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":"2026-08-06T23:04:09.666086Z","title":"Learning topology-agnostic eeg representations with geometry-aware modeling","venue":null,"work_id":"b10ae513-8271-4190-b379-bd2b64ca9097","year":2024},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:08.998549Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:d6303e64832642d818a50199e05a2b3edbbe9cd66a8fa228255691fffe060ea2","observation_id":"3909f0f3-7b9f-41e8-841f-cc040d9c7591","resolution":{"observed_at":"2026-08-06T23:04:09.671401Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.647847Z","title":"Coca: Contrastive captioners are image-text foundation models","venue":null,"work_id":"5ff1a81b-1fba-4998-a780-c21dab8b245b","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.006839Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:80f5a5657a57ca9d88442b5735463fbf02a1f6791377fbc11e29c5cf982a6875","observation_id":"c77bce5f-1b8b-4a68-b8d0-d968519f3285","resolution":{"observed_at":"2026-08-06T23:04:09.653896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.609414Z","title":"TS2Vec : Towards universal representation of time series","venue":null,"work_id":"d8a5893f-cbc0-4434-b8a4-7b04886ea251","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.012339Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:1d92c2a2c064331d32baf901f9a696794c39898dc867f314457c9621bd2d08ae","observation_id":"467d68e1-f2d1-4fef-a51f-c7d829ec4bd0","resolution":{"observed_at":"2026-08-06T23:04:09.622242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.589464Z","title":"and Yan, J","venue":null,"work_id":"b2b00dca-c496-4304-ab2b-7b2e71020e29","year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.017873Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:eb3e30a244f276b7b61d025f4e187d81f69616b9f44af3d078e4fc850560b11b","observation_id":"01a959df-ee49-4de6-a3e2-0cb05b3e48ae","resolution":{"observed_at":"2026-08-06T23:04:09.595267Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.567920Z","title":"I., and Wang, J","venue":null,"work_id":"bbedaa1f-6aed-4e15-b276-163c1da970aa","year":2023},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.023117Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:6c67f4ef5becf369d9821f59bb0eac7ba12b5830733ae577580e05e3c4cb9ed7","observation_id":"5d0a15a5-dee0-40e4-9363-10893b1a79e0","resolution":{"observed_at":"2026-08-06T23:04:09.574886Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.030157Z","title":"Informer: Beyond efficient transformer for long sequence time-series forecasting","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.030157Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:d6edd9a6a8284a9f9604f012f4a564ee4c10b95ebdd43735edc71ef724be2b09","observation_id":"7c053e5d-e4c8-478c-a11d-ee70999f9d1d","resolution":{"observed_at":"2026-08-06T23:04:09.030157Z","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":"2026-08-06T23:04:09.534738Z","title":"FEDformer : Frequency enhanced decomposed transformer for long-term series forecasting","venue":null,"work_id":"5c72ea59-30f5-4089-8bf3-2d7002fd0d11","year":2022},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.036325Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:e2fa8d1d7ad2aec27a1c0d7b833c97b31c787714bf9ea848218503ea43c54cca","observation_id":"c1bf5f04-55cf-4334-bca5-f36d103aa6ab","resolution":{"observed_at":"2026-08-06T23:04:09.541670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.511625Z","title":"Y., Yuhao Cui, D","venue":null,"work_id":"6122ed36-c58e-462e-b6eb-97221466b6fb","year":2019},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.042622Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:5a25bfbd0a77b8754644e1c0b6cbd202ee6b9cb8c31f86efd8cd5d13e56b743c","observation_id":"43728726-c5ed-44ee-ad21-39e5ba5cc7c6","resolution":{"observed_at":"2026-08-06T23:04:09.518729Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T23:04:09.057258Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-06T23:04:09.057258Z"},"links":{"citing_paper":"/paper/2506.20093"},"observation_digest":"sha256:953ef9b1e2cc077ba9ac2480cbfb31900e3f39f8c225021c04059b3a976f1499","observation_id":"6d05570d-e251-46be-88f4-5071354462a1","resolution":{"observed_at":"2026-08-06T23:04:09.057258Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.20093","last_updated":"2025-06-25T02:33:47Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T22:54:44.935282Z","submitted_at":"2025-06-25T02:33:47Z","title":"ITFormer: Bridging Time Series and Natural Language for Multi-Modal QA with Large-Scale Multitask Dataset"},"reference_resolution":{"displayed":57,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":21,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":57},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 57 of 57 outbound references and 7 inbound Pith citation observations for arXiv:2506.20093."}