{"as_of":"2026-08-07T19:35:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:21bb706ae86e9a98e7b1248c532ad8a6a75b5cc3411033232b6219104f8ae449","coverage":[{"denominator":30,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":30,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T21:15:10.572025Z","state":"measured"},{"denominator":30,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":30,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.00718/citation-record","integrity":"/paper/2507.00718/integrity","json":"/paper/2507.00718/citation-record.json","paper":"/paper/2507.00718"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T21:15:37.343255Z","title":"InProceedings of the 2024 Joint In- ternational Conference on Computational Linguis- tics, Language Resources and Evaluation (LREC- COLING 2024), pages 10124–10145","venue":null,"work_id":"b853ad6f-c687-4555-8f9e-ec5c66ab2d2b","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.460275Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:214f0aa8bbf16a3b3dc58c867f924118a2ad31d3257b3fe31e4e809c1fe504af","observation_id":"90531137-a916-4bd6-9c25-2ffc85a383a8","resolution":{"observed_at":"2026-08-06T21:15:37.363145Z","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":"2026-08-06T21:15:37.276448Z","title":null,"venue":null,"work_id":"4a51f405-2dc4-4423-9f60-7650413c29ed","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.504225Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:ade1210f4c927703f04e1d44d2995b2c662d308f5b116c57ffbd01b5764b9011","observation_id":"5be92e1a-b1a9-4a16-be0c-8ced10cf3c6d","resolution":{"observed_at":"2026-08-06T21:15:37.292345Z","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":"2406.18116","last_updated":"2024-06-26T07:07:52Z","snapshot_observed_at":"2026-07-06T18:37:08.729847Z","submitted_at":"2024-06-26T07:07:52Z","title":"BADGE: BADminton report Generation and Evaluation with LLM","version":1},"cited_work":{"arxiv_id":"2406.18116","doi":null,"metadata_source":"pith","pith_arxiv_id":"2406.18116","snapshot_observed_at":"2026-08-06T21:15:11.226995Z","title":"BADGE: BADminton report Generation and Evaluation with LLM","venue":"cs.CL","work_id":"95d5f709-4559-48ad-b622-c434f4458f2d","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.550168Z"},"links":{"cited_paper":"/paper/2406.18116","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:1d124a2bf16ff84039dc5720d21c961adfa3e11eed801f1e0aabbf6225a5a572","observation_id":"f2b8abc4-e189-4218-9ee8-66a48cca7bdb","resolution":{"observed_at":"2026-08-06T21:15:11.265195Z","resolver_source":"local_arxiv","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":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-07-06T18:55:11.576666Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-06T21:15:09.580564Z","title":"Elizabeth Fons, Rachneet Kaur, Soham Palande, Zhen Zeng, Tucker Balch, Manuela Veloso, and Svitlana Vyetrenko","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.580564Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:084fe790f3a738f04cb7d51e280e8f01d359b22164ea41e6ea25cf452f71edcd","observation_id":"1cf3395a-c10d-4ddc-8449-da3b012d91d7","resolution":{"observed_at":"2026-08-06T21:15:09.580564Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16563","last_updated":"2024-10-09T07:39:29Z","snapshot_observed_at":"2026-08-05T21:11:36.858345Z","submitted_at":"2024-04-25T12:24:37Z","title":"Evaluating Large Language Models on Time Series Feature Understanding: A Comprehensive Taxonomy and Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16563","snapshot_observed_at":"2026-08-06T21:15:09.624752Z","title":"Federal Reserve Bank of St","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.624752Z"},"links":{"cited_paper":"/paper/2404.16563","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:034dbb1fb40ea93ffb9e524ebb0afc9634fde07e4c75297dda96f6595fec78e5","observation_id":"b1225094-d564-42f9-9844-36f267d40443","resolution":{"observed_at":"2026-08-06T21:15:09.624752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01383","last_updated":"2025-05-14T06:05:53Z","snapshot_observed_at":"2026-08-05T04:27:47.515943Z","submitted_at":"2024-02-02T13:06:35Z","title":"LLM-based NLG Evaluation: Current Status and Challenges","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01383","snapshot_observed_at":"2026-08-06T21:15:09.677820Z","title":"Masayuki Kawarada, Tatsuya Ishigaki, and Hiroya Taka- mura","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.677820Z"},"links":{"cited_paper":"/paper/2402.01383","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:c20981f5f55eecd7ec402124c5ebdcaeaf34d7c54908efa0327096e2c952324e","observation_id":"c92c9f2f-38e8-4a68-8f9a-3be0a2615591","resolution":{"observed_at":"2026-08-06T21:15:09.677820Z","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":"2026-08-06T21:15:37.230318Z","title":"InPro- ceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 13190– 13200","venue":null,"work_id":"982e1e8e-807a-4aa7-90e4-a50ee32af997","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.720351Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:c08e993f4a29fdfb24189ce10bf309f575965915ee7e921aff46f3eedd18c073","observation_id":"d2b15512-0789-4b18-865e-b8d44fce0b20","resolution":{"observed_at":"2026-08-06T21:15:37.243807Z","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":"2026-08-06T21:15:37.179134Z","title":"InProceedings of the 2024 Joint International Conference on Compu- tational Linguistics, Language Resources and Evalu- ation (LREC-COLING 2024), pages 773–783","venue":null,"work_id":"4dfb27e3-b4f0-45b6-90b7-66dd79290d26","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.759259Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:765976bb1053294df5dc64c1470e603b8f198e65e876a7420b401aa501c23f7c","observation_id":"830e0c57-6bb6-4f65-910c-312cf4173c1b","resolution":{"observed_at":"2026-08-06T21:15:37.205020Z","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":"2026-08-06T21:15:37.108085Z","title":"InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track, pages 408–422","venue":null,"work_id":"ce3d4653-378c-467d-af54-54f0927a960c","year":2023},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.789106Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:68db5ddf0227fec326d62233e952bdb1fdec787a0153a0492b4b9e755b19f933","observation_id":"cc6c5d5b-182a-49aa-8b0b-487092318186","resolution":{"observed_at":"2026-08-06T21:15:37.139115Z","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":"2401.02982","last_updated":"2024-06-14T10:17:40Z","snapshot_observed_at":"2026-08-03T09:17:16.061212Z","submitted_at":"2024-01-01T15:26:23Z","title":"FinDABench: Benchmarking Financial Data Analysis Ability of Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.02982","snapshot_observed_at":"2026-08-06T21:15:09.830262Z","title":"Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.830262Z"},"links":{"cited_paper":"/paper/2401.02982","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:8e537da70be8f93e1c9c7db62746b836d4d586bd0090eac5a133585eaacde6e4","observation_id":"4df87185-9c90-4a76-be6b-d3af725daa9b","resolution":{"observed_at":"2026-08-06T21:15:09.830262Z","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":"2026-08-06T21:15:37.011148Z","title":"InProceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 2511–2522","venue":null,"work_id":"41695c56-3ab5-46a5-b0e8-35be0682c7ba","year":2023},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.873074Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:703537d77e81bfdf604fe76b40ae237121a838dba5fcf00043e0adc1afb0a5ce","observation_id":"62a60b45-325f-41c0-9435-b3e584e66bd0","resolution":{"observed_at":"2026-08-06T21:15:37.055417Z","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":"2406.11903","last_updated":"2024-06-15T16:11:35Z","snapshot_observed_at":"2026-07-06T18:32:28.184208Z","submitted_at":"2024-06-15T16:11:35Z","title":"A Survey of Large Language Models for Financial Applications: Progress, Prospects and Challenges","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.11903","snapshot_observed_at":"2026-08-06T21:15:09.928854Z","title":"Shunsuke Nishida, Yuki Zenimoto, Xiaotian Wang, Takuya Tamura, and Takehito Utsuro","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.928854Z"},"links":{"cited_paper":"/paper/2406.11903","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:d10bc80801f6d9751b1ce2577016ccde4f1d0e36eedd9f63b6bdff920f68e033","observation_id":"2fbfc671-1628-4df9-86f3-aac6645d56a4","resolution":{"observed_at":"2026-08-06T21:15:09.928854Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T21:15:09.978545Z","title":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei- Jing Zhu","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.978545Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:a679a90ab935659826dbb9013056dec4f6af4b975d9fca7f9b905fee41074ee5","observation_id":"d0e1f1b5-8b91-4c50-8bdd-fe6717a4b41d","resolution":{"observed_at":"2026-08-06T21:15:09.978545Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":"2026-08-06T21:15:10.034987Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.034987Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:7fec87c8fdf4bba8237b640deb96d85e007972f0065fc86e592b2eb0e741826f","observation_id":"200d6284-d1df-4565-bd25-dcceeb2e4f5d","resolution":{"observed_at":"2026-08-06T21:15:10.034987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.09288","last_updated":"2023-07-19T17:08:59Z","snapshot_observed_at":"2026-08-07T12:56:43.323460Z","submitted_at":"2023-07-18T14:31:57Z","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.09288","snapshot_observed_at":"2026-08-06T21:15:10.073323Z","title":"Shijie Wu, Ozan Irsoy, Steven Lu, Vadim Dabravolski, Mark Dredze, Sebastian Gehrmann, Prabhanjan Kam- badur, David Rosenberg, and Gideon Mann","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.073323Z"},"links":{"cited_paper":"/paper/2307.09288","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:bfe2e181e25878950a7d518ae07c6c4b83cb26e68d2263bdbadd1f483eb7b966","observation_id":"7972e8d4-24e8-46f6-88fd-8c63440b8d97","resolution":{"observed_at":"2026-08-06T21:15:10.073323Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.17564","last_updated":"2023-12-21T06:21:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-03-30T17:30:36Z","title":"BloombergGPT: A Large Language Model for Finance","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.17564","snapshot_observed_at":"2026-08-06T21:15:10.113038Z","title":"arXiv preprint arXiv:2303.17564","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.113038Z"},"links":{"cited_paper":"/paper/2303.17564","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:c4f064d2cd3787d989d27a2e461b23cd5ea7d0fa0f6d66096bef4b614d5c12e2","observation_id":"c5a5af36-0502-40ee-b9b8-add8c5f28a16","resolution":{"observed_at":"2026-08-06T21:15:10.113038Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.11025","last_updated":"2023-06-19T15:42:02Z","snapshot_observed_at":"2026-07-06T15:44:16.142806Z","submitted_at":"2023-06-19T15:42:02Z","title":"Temporal Data Meets LLM -- Explainable Financial Time Series Forecasting","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.11025","snapshot_observed_at":"2026-08-06T21:15:10.164820Z","title":"Tian Zhou, Peisong Niu, Liang Sun, Rong Jin, et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.164820Z"},"links":{"cited_paper":"/paper/2306.11025","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:7a4eb80674a70a756c458e8a636188112f7ab82012f94fce1bd7d7b2c39214af","observation_id":"c92b1f75-0204-41f2-8b25-38adcf944d88","resolution":{"observed_at":"2026-08-06T21:15:10.164820Z","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":"2026-08-06T21:15:36.831828Z","title":"Closing Prices: Date Close 2020-04-28 8607.7 2020-04-29 8914.7 2020-04-30 8889.6 2020-05-01 8605.0 Task: Long report generation with numerical technical indicators","venue":null,"work_id":"c7647caa-14f8-453c-bd6d-7a9f28cd1cae","year":2020},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.225004Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:1a8c3e8a06475ccbc94f3556fedda9edb20567db88f9481b4171467704475bda","observation_id":"b16bd4ea-ebdf-4c96-8486-a29e3b9a0328","resolution":{"observed_at":"2026-08-06T21:15:36.840739Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"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":"2026-08-06T21:15:36.768942Z","title":null,"venue":null,"work_id":"25ebbc67-a689-4714-a718-13cb07042826","year":2022},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.276308Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:51f6e4b6a4eda508ff9b6a74fab2157bede6a639c9020eaf4c311d2e0ca02bec","observation_id":"661f2233-6b49-4a4f-b6ee-6120f916499c","resolution":{"observed_at":"2026-08-06T21:15:36.792167Z","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":"2026-08-06T21:15:36.722290Z","title":"Despite these challenges, occasional recoveries occurred, indicating investor resilience","venue":null,"work_id":"a886cc60-c74b-40e1-81c6-928b1b85ab77","year":2022},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.308090Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:13950ab12bdce607fece5fcfadef0d714047fde6b6a1ca4190d22319f43bbc49","observation_id":"9ac865d2-4baf-4ffa-82f4-c70a0e984392","resolution":{"observed_at":"2026-08-06T21:15:36.739322Z","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":"2026-08-06T21:15:36.638640Z","title":null,"venue":null,"work_id":"4c7115fd-e154-47c0-abd9-448c6a479d6c","year":2022},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.344981Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:e725989f5a44501fd2de946f09e3d05ef7bc8993a1e2aa935e4d0b656ba69484","observation_id":"a40c60ae-10f5-4958-899d-159eb7c3588c","resolution":{"observed_at":"2026-08-06T21:15:36.683572Z","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":"2026-08-06T21:15:12.085651Z","title":"From July 2021 to December 2021, the index experienced a general upward trajectory, increasing from approximately 4250 to 4800","venue":null,"work_id":"41c4ceaf-9ac3-4903-87ae-65170ff8f726","year":2021},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.389445Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:469fac4581741715e73332b81927a709ccd112a98038e451a6f0e4e602bafd0c","observation_id":"86b4344c-c8ab-4586-a7a2-c313d53c2f9f","resolution":{"observed_at":"2026-08-06T21:15:12.133857Z","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":"2026-08-06T21:15:11.864676Z","title":null,"venue":null,"work_id":"397eff34-7419-4662-bd34-10ac91cfe49b","year":2021},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.455077Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:f0c5f239f4954afb16b2f5d4a45461e79e838d9f3816b4800f33d09e33b49226","observation_id":"7e342364-0504-4264-acf4-bfb0c0e3dd96","resolution":{"observed_at":"2026-08-06T21:15:11.911069Z","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":"2026-08-06T21:15:11.757639Z","title":"However, a modest recovery began in early December , as the index rebounded to close at 94.2 by December 25, 2024","venue":null,"work_id":"d8d1fb76-a229-4cd2-a690-43320c8715b9","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.499833Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:f97de09f2bbc6c15520f6d9d57685484d034724df81584bb9a69163535377da3","observation_id":"57bb3de0-8c8f-4473-ad1f-fa721b4b7c77","resolution":{"observed_at":"2026-08-06T21:15:11.780493Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"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":"2026-08-06T21:15:11.656398Z","title":"Despite this, the GMI remains relatively stable, exhibiting a volatility coefficient of 1.21 , indicating moderate price fluctuations","venue":null,"work_id":"49a138f7-7018-4066-b914-3a97d0ea918e","year":2025},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.534145Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:22eb4fa0392c0917ba528525058260994e2fd16614d64825e78ad845d151a3d2","observation_id":"5bd2176c-f21c-4c89-b060-828bbad45fd9","resolution":{"observed_at":"2026-08-06T21:15:11.698614Z","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":"2026-08-06T21:15:11.553978Z","title":"From January 1 to January 10, the index saw a gradual increase in closing prices, reaching a peak of 94.1","venue":null,"work_id":"1182c401-880c-4905-a323-e8aaa4fdeafc","year":2024},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.572025Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:e0fe30ff6d9dbf86631a0c33c5842d47182159e3656284cce68c35ddf90be4ae","observation_id":"ce0d6978-1997-4953-8ff9-325b4a1463ac","resolution":{"observed_at":"2026-08-06T21:15:11.613289Z","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":"2026-08-06T21:15:11.997921Z","title":"The index then experienced a correction, dropping below 4,300 by the end of November","venue":null,"work_id":"b3efde48-b7ef-4780-9545-70b362bd4a44","year":2021},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:10.425324Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:03225d9cf2c1b4ab47781e7473e4434fe90987fe8daae8366972ea03be205d3e","observation_id":"adb8cc80-a5ef-49cd-a8fd-2b3cd5eb27f8","resolution":{"observed_at":"2026-08-06T21:15:12.040872Z","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":"2026-08-06T21:15:36.880626Z","title":null,"venue":null,"work_id":"e06a9b2f-db53-45c2-81e6-3bee343703c0","year":1999},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.889705Z"},"links":{"citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:11024e3917f6a56ba6891a28d25fc77a1e545d94dab83377c0009819a217f122","observation_id":"11e995a6-d1f9-4dd8-989a-3c48d5066b71","resolution":{"observed_at":"2026-08-06T21:15:36.940548Z","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":"2310.08678","last_updated":"2023-10-12T19:28:57Z","snapshot_observed_at":"2026-07-06T16:32:11.601334Z","submitted_at":"2023-10-12T19:28:57Z","title":"Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.08678","snapshot_observed_at":"2026-08-06T21:15:09.523587Z","title":"Shang-Hsuan Chiang, Lin-Wei Chao, Kuang-Da Wang, Chih-Chuan Wang, and Wen-Chih Peng","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.523587Z"},"links":{"cited_paper":"/paper/2310.08678","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:56a90b965fc2531c6bebb56e4489c332e51f0a3ade94c17999b4fd6f0588c851","observation_id":"5c1581f7-ee77-47d1-a692-6101a01684a1","resolution":{"observed_at":"2026-08-06T21:15:09.523587Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-07-06T18:03:47.096406Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-06T21:15:09.406027Z","title":"Toyin D Aguda, Suchetha Siddagangappa, Elena Kochk- ina, Simerjot Kaur, Dongsheng Wang, and Charese Smiley","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T21:15:09.406027Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2507.00718"},"observation_digest":"sha256:86b1589e23bf96b9227ee5c11d904a5396cb6fca2006e229db903c0bcdd2e562","observation_id":"1b17a951-c123-4065-9ddd-cf447dac38aa","resolution":{"observed_at":"2026-08-06T21:15:09.406027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.00718","last_updated":"2025-07-01T12:57:18Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T21:06:22.857582Z","submitted_at":"2025-07-01T12:57:18Z","title":"AI Analyst: Framework and Comprehensive Evaluation of Large Language Models for Financial Time Series Report Generation"},"reference_resolution":{"displayed":30,"state_counts":{"malformed_identifier":2,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":10},"total_outbound_references":30},"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 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2507.00718."}