{"as_of":"2026-08-10T04:13:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5a1ad5ba0a44a775c5a1bc8775f0fee3a9cab620e8d2d9493a6dabdef94af84a","coverage":[{"denominator":83,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":83,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T11:48:52.090201Z","state":"measured"},{"denominator":83,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":83,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+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/2509.02241/citation-record","integrity":"/paper/2509.02241/integrity","json":"/paper/2509.02241/citation-record.json","paper":"/paper/2509.02241"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2401.14423","last_updated":"2024-05-05T00:54:26Z","snapshot_observed_at":"2026-08-08T12:36:30.073772Z","submitted_at":"2024-01-24T06:20:18Z","title":"Prompt Design and Engineering: Introduction and Advanced Methods","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.14423","snapshot_observed_at":"2026-08-05T11:48:42.499047Z","title":"arXiv preprint arXiv:2401.14423 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.499047Z"},"links":{"cited_paper":"/paper/2401.14423","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:e1b93f783871a9164c5df01d208b97cc4dcd1d16896f2d4580631feec82f8785","observation_id":"6b4ec868-c1a4-48f3-9c31-6a5627857548","resolution":{"observed_at":"2026-08-05T11:48:42.499047Z","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":"2026-08-05T11:48:42.596818Z","title":"Nature Reviews Physics5(5), 277–280 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.596818Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:747a10eaee623b4e753cd62814f74071c9b78db23e6f57f2441cc43f14546b57","observation_id":"dd9b54fb-824c-4ded-b287-c76a67579a79","resolution":{"observed_at":"2026-08-05T11:48:42.596818Z","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":"2026-08-05T11:48:42.651039Z","title":"Advances in neural information processing systems33, 1877–1901 (2020) 16 Klem et al","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.651039Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:bf2295a7d682742930050213d43367d8347c4b651cac43e3dbb1588ef3a721dd","observation_id":"b337fb89-b9d1-40c8-ac29-8dacbda300ce","resolution":{"observed_at":"2026-08-05T11:48:42.651039Z","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":"2026-08-05T11:48:42.713647Z","title":"think like a lawyer","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.713647Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:fa8d9f20d50c77128f37cd303a7ceca5bc52210ed36eb73da794069437855a1c","observation_id":"b294fb14-eb6f-4453-9ab5-be935048e40b","resolution":{"observed_at":"2026-08-05T11:48:42.713647Z","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":"2026-08-05T11:48:59.858993Z","title":"In: International Conference on Business Process Modeling, Development and Support","venue":null,"work_id":"0a471d56-e0d2-4493-84e0-6e72fbbf18cc","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.821294Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:fdeb5dcadfa1ed2edb3e1f59b765425c6e18dcdcf986f9d8c57d56f9fb2d149b","observation_id":"27cb9fa7-1324-477e-a2ae-7930f2fdf77d","resolution":{"observed_at":"2026-08-05T11:48:59.996195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:59.557804Z","title":"Amicus Curiae35, 28 (2001)","venue":null,"work_id":"e47d083c-d446-4d26-9f2c-0400ff2d61e8","year":2001},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.871927Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:c397dbfbc6eff88c2283200031f01c10463ac2b2343d2cdd51019daffec603f9","observation_id":"b320f782-524a-4275-a1f9-382ba32007dd","resolution":{"observed_at":"2026-08-05T11:48:59.687681Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.06204","last_updated":"2025-04-09T13:54:59Z","snapshot_observed_at":"2026-08-07T19:39:57.333135Z","submitted_at":"2024-06-26T16:34:33Z","title":"A Survey on Mixture of Experts in Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.06204","snapshot_observed_at":"2026-08-05T11:48:42.927210Z","title":"arXiv preprint arXiv:2407.06204 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:42.927210Z"},"links":{"cited_paper":"/paper/2407.06204","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:7200c1cf876227c8f618756a1c1a13dde8a87eff812f759c408ba68db9bddd65","observation_id":"13a8543b-f879-481e-bd18-90e33ffc9695","resolution":{"observed_at":"2026-08-05T11:48:42.927210Z","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":"2026-08-05T11:48:59.333274Z","title":"Metaverse Basic and Applied Research2, 33–33 (2023)","venue":null,"work_id":"42cbc344-fa33-4b8d-bebd-6a830e935ef0","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.015401Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:2b0eb140211d5593db3bb784e2e4a8db322947b9b28e4cd96c1f34a7c6fa7c11","observation_id":"0da0100d-40f9-4660-963a-302df9f36417","resolution":{"observed_at":"2026-08-05T11:48:59.439848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:59.042800Z","title":"IEEE Transactions on Knowledge and Data Engineering (2024)","venue":null,"work_id":"11ee9606-624b-479d-85a1-8bcf73fa4109","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.151861Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:40a1cfd447274436ea12d72333d0016f0c9cb4f5e9d586cbf0c44f2c965d2b4a","observation_id":"a80d6585-a877-4de9-8b8c-4c4a9cdd0c4f","resolution":{"observed_at":"2026-08-05T11:48:59.161061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.01322","last_updated":"2024-03-28T15:53:45Z","snapshot_observed_at":"2026-08-09T23:19:02.113499Z","submitted_at":"2024-03-28T15:53:45Z","title":"A Review of Multi-Modal Large Language and Vision Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.01322","snapshot_observed_at":"2026-08-05T11:48:43.288927Z","title":"arXiv preprint arXiv:2404.01322 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.288927Z"},"links":{"cited_paper":"/paper/2404.01322","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:71cc4445d4e6197fc6cab5fb5300717a07b16e01d943798648934c04a402e491","observation_id":"473f1fd4-803c-41fd-8dc1-524eea4a2891","resolution":{"observed_at":"2026-08-05T11:48:43.288927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.02559","last_updated":"2020-10-06T09:06:07Z","snapshot_observed_at":"2026-08-09T00:26:34.313498Z","submitted_at":"2020-10-06T09:06:07Z","title":"LEGAL-BERT: The Muppets straight out of Law School","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.02559","snapshot_observed_at":"2026-08-05T11:48:43.397449Z","title":"arXiv preprint arXiv:2010.02559 (2020)","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.397449Z"},"links":{"cited_paper":"/paper/2010.02559","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:22ca42b5e476d51a18e507d056b1e842fa3c39a1115075397863a7919e622ed3","observation_id":"fdeda45d-9f7f-4812-9517-f9da7b40d661","resolution":{"observed_at":"2026-08-05T11:48:43.397449Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2110.00976","last_updated":"2022-11-08T12:14:57Z","snapshot_observed_at":"2026-08-09T00:26:34.007324Z","submitted_at":"2021-10-03T10:50:51Z","title":"LexGLUE: A Benchmark Dataset for Legal Language Understanding in English","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2110.00976","snapshot_observed_at":"2026-08-05T11:48:43.528883Z","title":"arXiv preprint arXiv:2110.00976 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.528883Z"},"links":{"cited_paper":"/paper/2110.00976","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:1bd7df53ad719e7d28d7be895e84984f88f2a15e6f9e88ced84ea2a707765222","observation_id":"90d70973-e28e-46bd-9d55-1b409c5dd127","resolution":{"observed_at":"2026-08-05T11:48:43.528883Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00785","last_updated":"2024-04-13T22:02:23Z","snapshot_observed_at":"2026-08-04T16:19:28.848684Z","submitted_at":"2023-10-01T20:46:44Z","title":"BooookScore: A systematic exploration of book-length summarization in the era of LLMs","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00785","snapshot_observed_at":"2026-08-05T11:48:43.667193Z","title":"arXiv preprint arXiv:2310.00785 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.667193Z"},"links":{"cited_paper":"/paper/2310.00785","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:c72aab42c3724dee5eda9d63d43bd9939c2636b65e03397a26bb15565a6ba1b2","observation_id":"1b7d37ec-2acc-446d-8c0d-af7e1fac3899","resolution":{"observed_at":"2026-08-05T11:48:43.667193Z","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":"2026-08-05T11:48:58.773153Z","title":"Sublanguage: Studies of language in restricted semantic domains pp","venue":null,"work_id":"06120295-7a73-4570-a243-44eb6ff7068f","year":1982},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.846711Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:249574716bff4aaee07f9e417237b4df53380027d0a9961a8be4339dafd952ef","observation_id":"99a2951d-71ac-4a3e-ba3a-7f279b4d88a1","resolution":{"observed_at":"2026-08-05T11:48:58.926550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07468","last_updated":"2024-05-13T05:08:33Z","snapshot_observed_at":"2026-07-06T18:13:20.536375Z","submitted_at":"2024-05-13T05:08:33Z","title":"Evaluating large language models in medical applications: a survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.07468","snapshot_observed_at":"2026-08-05T11:48:43.975259Z","title":"arXiv preprint arXiv:2405.07468 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:43.975259Z"},"links":{"cited_paper":"/paper/2405.07468","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:166b9ad20bed6af009503aaae631eaa94cbcd7a9c0f1a2b09ca1875709d8c6b8","observation_id":"e27da6c9-b8ec-41e6-9714-eae61d865583","resolution":{"observed_at":"2026-08-05T11:48:43.975259Z","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":"2026-08-05T11:48:58.465384Z","title":"In: International Conference on Applications of Natural Language to Information Systems","venue":null,"work_id":"14ce5633-159f-4e36-97b8-86c1b47b7e7a","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:44.123374Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:19cb0643f1ac33978928c7d9a8a8221e340af188462ff99477a13387c6a123de","observation_id":"09ff07c4-0053-4379-90ae-b8ca58949056","resolution":{"observed_at":"2026-08-05T11:48:58.615138Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.00993","last_updated":"2021-09-15T07:56:26Z","snapshot_observed_at":"2026-08-06T01:11:39.232788Z","submitted_at":"2021-09-02T14:45:04Z","title":"LegaLMFiT: Efficient Short Legal Text Classification with LSTM Language Model Pre-Training","version":3},"cited_work":{"arxiv_id":"2109.00993","doi":null,"metadata_source":"pith","pith_arxiv_id":"2109.00993","snapshot_observed_at":"2026-08-05T11:48:54.323673Z","title":"LegaLMFiT: Efficient Short Legal Text Classification with LSTM Language Model Pre-Training","venue":"cs.CL","work_id":"7a35c932-9f02-46f2-b150-df580a5268b0","year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:44.299064Z"},"links":{"cited_paper":"/paper/2109.00993","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:23c861121ee6f0a5de5e7812bca4694e4248b96c72dd0b637552319d2aaba2d9","observation_id":"15454e58-daa1-44c2-b4dc-ba7da3410a1d","resolution":{"observed_at":"2026-08-05T11:48:54.375146Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1017/s0008197300124705","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T11:48:52.237923Z","title":"The Cambridge Law Journal5(3), 366–370 (1935)","venue":null,"work_id":"7cfaa950-26b8-4b3a-8aa7-46e1e3f019fb","year":1935},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:44.476696Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:b1c9bd7d9f75675181924cd0f2e8e0d5516540514fb80900e490687dfb11ed63","observation_id":"d4def78d-9f84-45fe-97f4-1d033d0f0969","resolution":{"observed_at":"2026-08-05T11:48:52.365891Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:58.230760Z","title":"In: The Thirty-eighth Annual Conference on Neural Information Processing Systems (2024)","venue":null,"work_id":"34b62882-fcbd-4986-8354-3980b40d2eb2","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:44.649953Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:bbc159b65cd3552d43096688732b828a1d1606c115386f51c8f71282b43082ca","observation_id":"48269ae0-3403-49fc-831c-b288ac004e90","resolution":{"observed_at":"2026-08-05T11:48:58.344195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.03883","last_updated":"2024-03-07T06:39:32Z","snapshot_observed_at":"2026-08-08T14:59:42.793324Z","submitted_at":"2024-03-06T17:42:16Z","title":"SaulLM-7B: A pioneering Large Language Model for Law","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.03883","snapshot_observed_at":"2026-08-05T11:48:44.861535Z","title":"arXiv preprint arXiv:2403.03883 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:44.861535Z"},"links":{"cited_paper":"/paper/2403.03883","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:6ff043576353f8abf5ba52925b3fc3933c07621dd80266b4f1118cb7dcd8b1ee","observation_id":"72afe5d3-8673-43ff-8636-e7d7c88445f2","resolution":{"observed_at":"2026-08-05T11:48:44.861535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2306.16092","last_updated":"2026-06-08T08:40:57Z","snapshot_observed_at":"2026-07-06T15:47:45.886474Z","submitted_at":"2023-06-28T10:48:34Z","title":"Chatlaw: A Multi-Agent Legal Assistant based on a Role-Aligned Mixture-of-Experts Architecture","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.16092","snapshot_observed_at":"2026-08-05T11:48:45.028189Z","title":"arXiv preprint arXiv:2306.16092 (2023) LLMs for LLMs 17","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:45.028189Z"},"links":{"cited_paper":"/paper/2306.16092","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:09bfe92060cd19756884f37fcd4f1052260be64f9bb16f2902a79aaa3c6e011f","observation_id":"bfa5f108-0db2-4cd2-8452-14e0457a1385","resolution":{"observed_at":"2026-08-05T11:48:45.028189Z","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":"2026-08-05T11:48:57.999380Z","title":"In: Companion Proceedings of the 29th International Conference on Intelligent User Interfaces","venue":null,"work_id":"55673f2f-488c-41db-b754-4f98bc591010","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:45.209791Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:0ebad5b0ceaf439d22c2dc4bac7f6957b0306c9f9c6a363bc756619a58f224f8","observation_id":"3f3da29d-f213-427b-9f7f-2b16ba96ecd5","resolution":{"observed_at":"2026-08-05T11:48:58.116395Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.12246","last_updated":"2024-07-21T08:01:00Z","snapshot_observed_at":"2026-08-10T03:46:12.433693Z","submitted_at":"2023-02-23T18:58:59Z","title":"Active Prompting with Chain-of-Thought for Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.12246","snapshot_observed_at":"2026-08-05T11:48:45.394668Z","title":"arXiv preprint arXiv:2302.12246 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:45.394668Z"},"links":{"cited_paper":"/paper/2302.12246","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:c99c2c38c39f1fd461cc5d7210339b0ad361b7c6fd2e6519569ec7dad512b25e","observation_id":"31f2cf86-fc70-4e7f-aab6-1794523522c1","resolution":{"observed_at":"2026-08-05T11:48:45.394668Z","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":"2026-08-05T11:48:57.760088Z","title":"Authorea Preprints (2023)","venue":null,"work_id":"0b19541a-11e4-4ef6-bfe0-459757901746","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:45.581023Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:061b54798fdb8099089801d61eada9e47184ad569ff8bd32a2b36e4b8d716e02","observation_id":"51379b3f-3432-400f-aff3-c04f84111752","resolution":{"observed_at":"2026-08-05T11:48:57.899020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:57.531136Z","title":"In: Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining (KDD ’96)","venue":null,"work_id":"e724fd31-310d-4ec5-9950-425f565add92","year":1996},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:45.790759Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:118a1d86cdad5db63086c6337ec3ee3733d93e6e77eaff0f0db4c478f1a9f67f","observation_id":"5470c87e-33cf-4b36-b0ed-acd70a1c3bfa","resolution":{"observed_at":"2026-08-05T11:48:57.650956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-05T11:48:46.010947Z","title":"arXiv preprint arXiv:2312.10997 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.010947Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:60f610daa3c3a945a3e90236ddd7724c485b624afca9f05eebef8e4c3015fc69","observation_id":"d96b6ac6-65fe-450d-bb6c-90b0524e0f83","resolution":{"observed_at":"2026-08-05T11:48:46.010947Z","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":"2026-08-05T11:48:57.339801Z","title":"Annals of biomedical engineering51(12), 2629–2633 (2023)","venue":null,"work_id":"e52dff31-ef62-47e4-8311-dd65743b2dcf","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.154948Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:6690c9859c1288de947a6bbafa3c7d5357231ef7179f64f104a9bac352913003","observation_id":"900f156c-3904-4c01-955e-e15c19ea4ff6","resolution":{"observed_at":"2026-08-05T11:48:57.412195Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.06120","last_updated":"2022-09-13T16:11:54Z","snapshot_observed_at":"2026-08-09T21:55:02.274197Z","submitted_at":"2022-09-13T16:11:54Z","title":"LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2209.06120","snapshot_observed_at":"2026-08-05T11:48:46.286210Z","title":"arXiv preprint arXiv:2209.06120 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.286210Z"},"links":{"cited_paper":"/paper/2209.06120","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:15aa9de78f2566df179eff09c2d55a071b85c01617f5cb34d13bcb758b8a6f6c","observation_id":"0bce9b16-1f3d-4668-9c7e-70743afe2a88","resolution":{"observed_at":"2026-08-05T11:48:46.286210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2103.06268","last_updated":"2021-11-08T21:23:22Z","snapshot_observed_at":"2026-08-09T00:26:30.748246Z","submitted_at":"2021-03-10T18:59:34Z","title":"CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.06268","snapshot_observed_at":"2026-08-05T11:48:46.438334Z","title":"arXiv preprint arXiv:2103.06268 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.438334Z"},"links":{"cited_paper":"/paper/2103.06268","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3e957569e2b58d12aa1ab0d69dc0e5b626db8581305fe6973c85815b7e1a02ae","observation_id":"76978a21-fdff-4007-b164-429ccfe44fca","resolution":{"observed_at":"2026-08-05T11:48:46.438334Z","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":"2026-08-05T11:48:57.083288Z","title":"International Medical Education 2(3), 198–205 (2023)","venue":null,"work_id":"1bb8fea1-ec1b-4f41-9b39-2063c9a9c048","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.626898Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:49e8cbbc340dc01de7925bffe1d4fb7830f8cb58ce4eaf36c6225e755eb38e7a","observation_id":"f2dc924d-fe40-4105-ac81-8331e5c2abd6","resolution":{"observed_at":"2026-08-05T11:48:57.197704Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:56.979116Z","title":"In: European Conference on Information Retrieval","venue":null,"work_id":"b7e52461-3ea4-42de-b7ac-047385b8d76e","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.775347Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:08cffb4a0b28f4ce1fcd4efbf7256d79f27113108c4fd7cc003e6fee5a6a25b2","observation_id":"abca8bac-8b69-47d5-a590-f5074d5f1171","resolution":{"observed_at":"2026-08-05T11:48:57.027166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15062","last_updated":"2023-10-14T02:14:51Z","snapshot_observed_at":"2026-07-06T15:32:25.931739Z","submitted_at":"2023-05-24T11:52:07Z","title":"Lawyer LLaMA Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15062","snapshot_observed_at":"2026-08-05T11:48:46.938321Z","title":"arXiv preprint arXiv:2305.15062 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:46.938321Z"},"links":{"cited_paper":"/paper/2305.15062","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3d6b538092a279d5e4ed7bedc6139d1b5292bfcffad8fd740a826d3f254ef647","observation_id":"c43fd66b-dfd8-48e8-a6a3-182fcda74818","resolution":{"observed_at":"2026-08-05T11:48:46.938321Z","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":"2026-08-05T11:48:56.851714Z","title":"In: European semantic web conference","venue":null,"work_id":"0d900679-6d05-4231-99ba-46f32f99fd82","year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.107885Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3c819902e99c581ccef2e52ba984fd88aa43bf14195ded4e0d461dbf7c220647","observation_id":"4ec13962-d15f-40b3-becc-8e272bc5314c","resolution":{"observed_at":"2026-08-05T11:48:56.917896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.16883","last_updated":"2023-07-31T17:49:18Z","snapshot_observed_at":"2026-08-05T00:07:31.362950Z","submitted_at":"2023-07-31T17:49:18Z","title":"HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attribution","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.16883","snapshot_observed_at":"2026-08-05T11:48:47.254595Z","title":"arXiv preprint arXiv:2307.16883 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.254595Z"},"links":{"cited_paper":"/paper/2307.16883","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:7c79bf10a9b4fbd4b98971d1b729f890c0aa895c1ba8378ed0a8e72fbb541888","observation_id":"ef882831-6f81-485b-a7a8-6d7825f42bff","resolution":{"observed_at":"2026-08-05T11:48:47.254595Z","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":"2026-08-05T11:48:56.706853Z","title":"In: JSAI International Symposium on Artificial Intelligence","venue":null,"work_id":"31541ce8-7e3f-4f94-a85a-8a354af09cc4","year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.406592Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:20b167744a9f194a4afd596a4232133816d035927f49259202ef16cce8405c3e","observation_id":"b4089498-02db-46c0-8a10-5f443ff49d7e","resolution":{"observed_at":"2026-08-05T11:48:56.774338Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03718","last_updated":"2023-11-26T00:48:12Z","snapshot_observed_at":"2026-08-06T21:35:45.212216Z","submitted_at":"2023-11-26T00:48:12Z","title":"Large Language Models in Law: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.03718","snapshot_observed_at":"2026-08-05T11:48:47.548791Z","title":"arXiv preprint arXiv:2312.03718 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.548791Z"},"links":{"cited_paper":"/paper/2312.03718","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:335a6f4a1ff575f16f8aa06a5b4028a665284080695bdc21a5d6fa27a292a3b9","observation_id":"6f9ea028-1553-4816-9cc8-6d7f0bf68c06","resolution":{"observed_at":"2026-08-05T11:48:47.548791Z","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":"2026-08-05T11:48:56.555310Z","title":null,"venue":null,"work_id":"097af4fb-15ef-4f65-a8b2-dcdb4f7f2772","year":2016},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.724345Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:96da67b86abcf194ee6fb09958681719e671aba448288c0041f6c5e8021cfe65","observation_id":"f60023c1-a56a-42b0-b090-1fd0db3ac844","resolution":{"observed_at":"2026-08-05T11:48:56.631790Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.10386","last_updated":"2020-10-20T15:50:50Z","snapshot_observed_at":"2026-08-09T08:57:22.323802Z","submitted_at":"2020-10-20T15:50:50Z","title":"A Benchmark for Lease Contract Review","version":1},"cited_work":{"arxiv_id":"2010.10386","doi":null,"metadata_source":"pith","pith_arxiv_id":"2010.10386","snapshot_observed_at":"2026-08-05T11:48:54.025669Z","title":"A Benchmark for Lease Contract Review","venue":"cs.IR","work_id":"aef698c4-8307-4c90-b598-cbd35406c421","year":2020},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:47.865686Z"},"links":{"cited_paper":"/paper/2010.10386","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:a57938e3f410e61fcf1ef1e80d04860b3de7adaad6903e478d57092d4704ed76","observation_id":"dce984a3-957a-49c1-b292-b68676bfafa3","resolution":{"observed_at":"2026-08-05T11:48:54.103624Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00190","last_updated":"2021-01-01T08:00:36Z","snapshot_observed_at":"2026-07-06T10:29:18.734092Z","submitted_at":"2021-01-01T08:00:36Z","title":"Prefix-Tuning: Optimizing Continuous Prompts for Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.00190","snapshot_observed_at":"2026-08-05T11:48:48.018159Z","title":"arXiv preprint arXiv:2101.00190 (2021)","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.018159Z"},"links":{"cited_paper":"/paper/2101.00190","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3792aa5be7ffdcc3975f7cf14da731e4d050b03e39c45efeb7fec0b5a78a9887","observation_id":"6b58c4be-8611-4ebf-8a3f-8843f6e978d6","resolution":{"observed_at":"2026-08-05T11:48:48.018159Z","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":"2026-08-05T11:48:56.436333Z","title":"Advances in Neural Information Processing Systems36 (2024)","venue":null,"work_id":"70db8106-d8c4-43ff-aab8-2a9268375d59","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.205505Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:f3807b50d0eb7c5d1f258b48279e879a73a079bebff3c32ba1ab99c4237479c5","observation_id":"b22e5db2-5e5d-49b5-9897-4eb04c9cc184","resolution":{"observed_at":"2026-08-05T11:48:56.491533Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:48.404001Z","title":"Transactions of the Association for Computational Linguistics12, 157–173 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.404001Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:a80d79d0c68034f30bb48247858e9df7f9191970124293fdbda39ed0f51c2e27","observation_id":"c850a325-99fd-44bf-8dae-f9fe4446130c","resolution":{"observed_at":"2026-08-05T11:48:48.404001Z","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":"2026-08-05T11:48:56.289630Z","title":"The Journal of Academic Librarianship49(4), 102720 (2023) 18 Klem et al","venue":null,"work_id":"aba5d19b-acf1-412a-a642-1276ef1710a7","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.569956Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:28a648178e3af6e8a1da31a3d0e3c3a40e25b676dbb11c8a45ee05ecf0f81e3d","observation_id":"d98f20e9-2393-420c-b874-dcae860f7022","resolution":{"observed_at":"2026-08-05T11:48:56.357155Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.07209","last_updated":"2022-02-15T06:01:36Z","snapshot_observed_at":"2026-08-03T17:08:55.953364Z","submitted_at":"2022-02-15T06:01:36Z","title":"Case law retrieval: problems, methods, challenges and evaluations in the last 20 years","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.07209","snapshot_observed_at":"2026-08-05T11:48:48.796849Z","title":"arXiv preprint arXiv:2202.07209 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.796849Z"},"links":{"cited_paper":"/paper/2202.07209","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:a7bb86309bead6c5b5b36d039086c6d7c04c807a4b358521ea07cdeb2d0e6e2a","observation_id":"de57ca33-258f-4fe4-af31-e352ea34d4e5","resolution":{"observed_at":"2026-08-05T11:48:48.796849Z","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":"2026-08-05T11:48:56.154321Z","title":"In: Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval","venue":null,"work_id":"b9e5acc2-9d81-4cce-b23e-8a9dc74044ec","year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:48.948215Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:2d457c42046760b9bbadfa1f1f585b3c9acff7a1ce99e42740da56f58f417042","observation_id":"8da12771-e874-4205-b94c-a3a5d3b9a1bb","resolution":{"observed_at":"2026-08-05T11:48:56.205639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2105.13562","last_updated":"2021-05-31T11:17:43Z","snapshot_observed_at":"2026-07-06T11:13:32.596343Z","submitted_at":"2021-05-28T03:07:32Z","title":"ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation","version":2},"cited_work":{"arxiv_id":"2105.13562","doi":null,"metadata_source":"pith","pith_arxiv_id":"2105.13562","snapshot_observed_at":"2026-08-05T11:48:53.875628Z","title":"ILDC for CJPE: Indian Legal Documents Corpus for Court Judgment Prediction and Explanation","venue":"cs.CL","work_id":"897715b9-4ca4-40f5-8fc5-2ef9613a3526","year":2021},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.103590Z"},"links":{"cited_paper":"/paper/2105.13562","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:48a7af6ddcda03a11a480fa87961062d33c875579e759b3afb1485a1672a908b","observation_id":"30bedc67-64bd-4110-af9a-24976badfdc7","resolution":{"observed_at":"2026-08-05T11:48:53.920538Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:56.018833Z","title":"In: International Conference on Artificial Intelligence in Education","venue":null,"work_id":"bff895a8-98b7-463c-949c-788b6710750b","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.254624Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:1bf23504364319c31baa0c40ca91ebdfa58847b75fcf2bacbdcee568b916520d","observation_id":"46b201bf-6d50-468c-8800-71002e02f249","resolution":{"observed_at":"2026-08-05T11:48:56.085636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.09906","last_updated":"2025-03-03T04:28:49Z","snapshot_observed_at":"2026-07-06T17:30:34.153488Z","submitted_at":"2024-02-15T12:12:19Z","title":"Generative Representational Instruction Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.09906","snapshot_observed_at":"2026-08-05T11:48:49.394046Z","title":"arXiv preprint arXiv:2402.09906 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.394046Z"},"links":{"cited_paper":"/paper/2402.09906","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:0998874077dc4ad9530cbb9b8b56c33629c7ea81c49218bdf3ead01ef43ed363","observation_id":"f9723e54-1400-4474-98d3-be84c55d71b2","resolution":{"observed_at":"2026-08-05T11:48:49.394046Z","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":"2026-08-05T11:48:55.858227Z","title":"Southeast Europe Journal of Soft Computing12(1), 13–41 (2023)","venue":null,"work_id":"c4fc677c-4484-4fca-8041-5760d4355463","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.557919Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:53393ac4af06d5ffe6ad3bc12a514a9d953eb0a00c3f5a75fd700d5df2600587","observation_id":"a4d2765c-f856-44b2-9387-3e1757e188b3","resolution":{"observed_at":"2026-08-05T11:48:55.929334Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.05729","last_updated":"2023-02-14T06:26:42Z","snapshot_observed_at":"2026-08-04T09:16:51.971081Z","submitted_at":"2023-02-11T15:50:20Z","title":"A Brief Report on LawGPT 1.0: A Virtual Legal Assistant Based on GPT-3","version":2},"cited_work":{"arxiv_id":"2302.05729","doi":null,"metadata_source":"pith","pith_arxiv_id":"2302.05729","snapshot_observed_at":"2026-08-05T11:48:53.663115Z","title":"A Brief Report on LawGPT 1.0: A Virtual Legal Assistant Based on GPT-3","venue":"cs.CL","work_id":"9c1f6782-5193-468e-9b64-d21b2233d897","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.719250Z"},"links":{"cited_paper":"/paper/2302.05729","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:179c7d01c37544235d760e84f39eaff2d2fe571850215b9d4bafd17a201b5a5e","observation_id":"3baa347e-d545-461b-b5ae-c15484e504dd","resolution":{"observed_at":"2026-08-05T11:48:53.749347Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.02069","last_updated":"2024-05-19T12:40:36Z","snapshot_observed_at":"2026-07-06T15:37:31.493443Z","submitted_at":"2023-06-03T10:10:38Z","title":"MultiLegalPile: A 689GB Multilingual Legal Corpus","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.02069","snapshot_observed_at":"2026-08-05T11:48:49.845504Z","title":"arXiv preprint arXiv:2306.02069 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.845504Z"},"links":{"cited_paper":"/paper/2306.02069","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:406d1d587c15e0c782a9f70e0f1da20ce2eba365f0980245e01ffee246b60fb3","observation_id":"76782ba9-0a8b-4cd2-9099-b2c33d225410","resolution":{"observed_at":"2026-08-05T11:48:49.845504Z","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":"2026-08-05T11:48:55.756353Z","title":null,"venue":null,"work_id":"533ac5f8-ac23-4ffb-a53c-e5213133d638","year":null},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.901228Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:d7379f9de2eed2b9cff2de8bd19b5a6c960d66b638c55f822648bc362f1ee8ab","observation_id":"5f360268-c1d7-4cf0-9807-c31ddfd15e8f","resolution":{"observed_at":"2026-08-05T11:48:55.800906Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:55.628169Z","title":"Behaviour & Information Technology pp","venue":null,"work_id":"74cc3a50-822e-4c6b-988b-c233a04641a6","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:49.966932Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:cb48f108ae5cc0f820ffed80e1bafc6edb59a8853faffdf96511543cbc2a9a0f","observation_id":"f67eb5ec-37f0-4388-ad88-34cd0b9c55db","resolution":{"observed_at":"2026-08-05T11:48:55.690514Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:55.485683Z","title":null,"venue":null,"work_id":"0514b56a-6e3b-4bc4-babd-9e48decfb952","year":2019},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.035884Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:9739f642834c90ba3203e322b44cdb59a5ea6f64121f26e2469f4ca3a36baa88","observation_id":"6d981b0c-fd87-4b19-8711-05a16f21c541","resolution":{"observed_at":"2026-08-05T11:48:55.550598Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.00071","last_updated":"2026-02-06T19:40:50Z","snapshot_observed_at":"2026-08-01T02:15:47.181936Z","submitted_at":"2023-08-31T18:18:07Z","title":"YaRN: Efficient Context Window Extension of Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.00071","snapshot_observed_at":"2026-08-05T11:48:50.110653Z","title":"arXiv preprint arXiv:2309.00071 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.110653Z"},"links":{"cited_paper":"/paper/2309.00071","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:50447bf53b8dc0da56d06a906d7a03f31fa3b44725a4505d98812bb36a4bc20b","observation_id":"4d38aef6-eaaa-4a99-90c1-2ba0e9c708fb","resolution":{"observed_at":"2026-08-05T11:48:50.110653Z","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":"2026-08-05T11:48:55.343082Z","title":"In: Legal Knowledge and Information Systems, pp","venue":null,"work_id":"da85704b-7a65-4a77-80b2-bc88331ee6cb","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.178702Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:7eeef13e733dbb4d834ff5cfac922f0cb5bb284fe8d13906a9562a47e6039eff","observation_id":"d4869cbe-b56a-43d4-91bf-b8622da288d2","resolution":{"observed_at":"2026-08-05T11:48:55.405073Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07927","last_updated":"2025-03-16T06:23:34Z","snapshot_observed_at":"2026-08-05T17:55:26.008016Z","submitted_at":"2024-02-05T19:49:13Z","title":"A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07927","snapshot_observed_at":"2026-08-05T11:48:50.229826Z","title":"arXiv preprint arXiv:2402.07927 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.229826Z"},"links":{"cited_paper":"/paper/2402.07927","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:73d0eb9628535d031d5152f89dbfd24466ef80faef5c6912e11fa230a0f7093e","observation_id":"6ff94372-74e3-41d4-8b95-3e888c1dc2d8","resolution":{"observed_at":"2026-08-05T11:48:50.229826Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.11430","last_updated":"2023-10-24T22:50:02Z","snapshot_observed_at":"2026-08-03T12:05:37.562875Z","submitted_at":"2023-05-19T04:59:34Z","title":"TELeR: A General Taxonomy of LLM Prompts for Benchmarking Complex Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.11430","snapshot_observed_at":"2026-08-05T11:48:50.306575Z","title":"arXiv preprint arXiv:2305.11430 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.306575Z"},"links":{"cited_paper":"/paper/2305.11430","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:df2d54dfdb6ff3656240664d53bcd9901467a470d505c9c083c470dcf2770ba5","observation_id":"35115b91-8aee-4b67-86ac-cdb85e1b7c86","resolution":{"observed_at":"2026-08-05T11:48:50.306575Z","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":"2026-08-05T11:48:55.203527Z","title":"In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval","venue":null,"work_id":"182c6cd6-f73b-499d-85ae-76cd9ac778f8","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.381562Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:dcb1bf5232f1ef12b1ead8a1f4cb00e010ceea2d5f49086624db1d7cd1d56e45","observation_id":"1b007cc2-a2c5-40b9-80a2-226684051b03","resolution":{"observed_at":"2026-08-05T11:48:55.270994Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:55.051601Z","title":null,"venue":null,"work_id":"19977859-87ff-4dd7-9d0a-42b55e7a9438","year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.452791Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:a260de3d4bfa3da911046aa319a85d39feb7ebc14aeef53d3ecc25fc49f36a75","observation_id":"94d4b875-2323-4700-bb78-ccf584e3c10a","resolution":{"observed_at":"2026-08-05T11:48:55.124092Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.07544","last_updated":"2022-10-14T05:43:08Z","snapshot_observed_at":"2026-08-04T10:56:38.782033Z","submitted_at":"2022-10-14T05:43:08Z","title":"Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation","version":1},"cited_work":{"arxiv_id":"2210.07544","doi":null,"metadata_source":"pith","pith_arxiv_id":"2210.07544","snapshot_observed_at":"2026-08-05T11:48:53.466607Z","title":"Legal Case Document Summarization: Extractive and Abstractive Methods and their Evaluation","venue":"cs.CL","work_id":"f7e6ae40-f35d-4ccb-b7ca-6c5d3f68b46d","year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.530701Z"},"links":{"cited_paper":"/paper/2210.07544","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:909ee613f8e6f1519d6ee581137f26c93091e9580116848464d18ced680faf10","observation_id":"b2fa638f-0094-4f3b-b796-86b7a2b50bdd","resolution":{"observed_at":"2026-08-05T11:48:53.532902Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:54.943576Z","title":"one country, two systems","venue":null,"work_id":"30b4619e-9678-4696-810d-52428f75fde5","year":2011},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.611738Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3befa52505adf0a3d286cbbe5afd47cbace6d3fcda899914157951f16624b9b2","observation_id":"6a418dd3-fb68-4643-b7b6-e09d1d194bc9","resolution":{"observed_at":"2026-08-05T11:48:54.996485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:50.677378Z","title":"Neurocomputing568, 127063 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.677378Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3423a18b6d580fcf77f82945e8af97a71dc847cc172e6b0f6e16e502933ec97d","observation_id":"55355070-670c-4941-bda7-45bb22dc1a85","resolution":{"observed_at":"2026-08-05T11:48:50.677378Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.16252","last_updated":"2024-12-16T05:53:28Z","snapshot_observed_at":"2026-07-06T18:50:31.528338Z","submitted_at":"2024-07-23T07:40:41Z","title":"LawLuo: A Multi-Agent Collaborative Framework for Multi-Round Chinese Legal Consultation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.16252","snapshot_observed_at":"2026-08-05T11:48:50.732611Z","title":"arXiv preprint arXiv:2407.16252 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.732611Z"},"links":{"cited_paper":"/paper/2407.16252","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:c50ec1662c967a1a745659e4306bbe3a355233134bdeab4d3c0787507ac236d3","observation_id":"137f49c3-7bf0-48a2-abef-67db946e87bd","resolution":{"observed_at":"2026-08-05T11:48:50.732611Z","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":"2026-08-05T11:48:50.786987Z","title":"Nature medicine29(8), 1930–1940 (2023)","venue":null,"work_id":null,"year":1930},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.786987Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:2aacb971e2e16ff3787d57ebf861e3178c080ee17b5f8f2619f93b8720cd06f1","observation_id":"fa66006f-fd29-4963-ab19-ec825fa0b713","resolution":{"observed_at":"2026-08-05T11:48:50.786987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.02199","last_updated":"2022-12-05T12:17:02Z","snapshot_observed_at":"2026-07-06T14:26:51.875190Z","submitted_at":"2022-12-05T12:17:02Z","title":"Legal Prompt Engineering for Multilingual Legal Judgement Prediction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.02199","snapshot_observed_at":"2026-08-05T11:48:50.856145Z","title":"arXiv preprint arXiv:2212.02199 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.856145Z"},"links":{"cited_paper":"/paper/2212.02199","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:424b60a7ef1a9e858aa33a5a0fba43438a867dc48e8dc32fe10eb5e52614bf9a","observation_id":"71b3b313-5ba9-4acc-8525-a9b3eec1d214","resolution":{"observed_at":"2026-08-05T11:48:50.856145Z","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":"2026-08-05T11:48:54.795415Z","title":"Meta-Radiology p","venue":null,"work_id":"1fc54b84-c1ac-4df3-80c5-e1d8e79f169f","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.913381Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:f25d1899834d7ff805ad7acba67919ecf47c36dd2ebfd16da9ff17f0cd55b164","observation_id":"f119e0be-6cf0-459f-9def-39e4b3c0a9c1","resolution":{"observed_at":"2026-08-05T11:48:54.854645Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2304.14670","last_updated":"2024-03-23T10:10:18Z","snapshot_observed_at":"2026-07-06T15:21:04.733820Z","submitted_at":"2023-04-28T08:03:42Z","title":"Prompt Engineering for Healthcare: Methodologies and Applications","version":2},"cited_work":{"arxiv_id":"2304.14670","doi":null,"metadata_source":"pith","pith_arxiv_id":"2304.14670","snapshot_observed_at":"2026-08-05T11:48:53.237968Z","title":"Prompt Engineering for Healthcare: Methodologies and Applications","venue":"cs.AI","work_id":"7f152ec9-bb7c-403a-b55c-ea9b981c7fe3","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:50.996705Z"},"links":{"cited_paper":"/paper/2304.14670","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:687d1d0a65d7378b83e2971bfc5f4b4eb025e5f6563825b83ba137cf0564c8a9","observation_id":"0cf1390a-193a-489b-acc7-a722bd7cd2b0","resolution":{"observed_at":"2026-08-05T11:48:53.301379Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2203.11171","last_updated":"2023-03-07T17:57:37Z","snapshot_observed_at":"2026-07-06T12:50:22.773056Z","submitted_at":"2022-03-21T17:48:52Z","title":"Self-Consistency Improves Chain of Thought Reasoning in Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2203.11171","snapshot_observed_at":"2026-08-05T11:48:51.052744Z","title":"arXiv preprint arXiv:2203.11171 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.052744Z"},"links":{"cited_paper":"/paper/2203.11171","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:acf3f5af513f9c320e013d59dfec1a2b8e4742e801cdbc170bb5005afaf5bd3c","observation_id":"f8bcb1a1-1d6c-4285-af60-f38557f9abfc","resolution":{"observed_at":"2026-08-05T11:48:51.052744Z","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":"2026-08-05T11:48:51.113397Z","title":"Advances in neural information processing systems35, 24824–24837 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.113397Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:4d662210bc6d317c61d53dd3b0cb4a4bda3a96a79d3b297910a004ae7258ac0c","observation_id":"0ecf19d4-1f54-4c1d-90a0-96f4c2dc277d","resolution":{"observed_at":"2026-08-05T11:48:51.113397Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.11382","last_updated":"2023-02-21T12:42:44Z","snapshot_observed_at":"2026-07-06T14:54:37.559648Z","submitted_at":"2023-02-21T12:42:44Z","title":"A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.11382","snapshot_observed_at":"2026-08-05T11:48:51.181923Z","title":"arXiv preprint arXiv:2302.11382 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.181923Z"},"links":{"cited_paper":"/paper/2302.11382","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:f3b825cd54161195ddc861e04569ec4ecffd18846651edb1197a16c95c93c03f","observation_id":"054db707-a38d-4f37-a002-f7e2553413b5","resolution":{"observed_at":"2026-08-05T11:48:51.181923Z","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":"2026-08-05T11:48:51.259128Z","title":"arXiv preprint arXiv:2303.17564 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.259128Z"},"links":{"cited_paper":"/paper/2303.17564","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:02d7463a515152318c719df7810f4abc1e6a42ea6cae5d58f26e1bfee2d718d6","observation_id":"9e25c5e2-6ba8-45cf-9f80-fe491413890a","resolution":{"observed_at":"2026-08-05T11:48:51.259128Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.08962","last_updated":"2019-11-25T14:26:52Z","snapshot_observed_at":"2026-08-06T16:39:46.976981Z","submitted_at":"2019-11-20T15:23:59Z","title":"CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain","version":3},"cited_work":{"arxiv_id":"1911.08962","doi":null,"metadata_source":"pith","pith_arxiv_id":"1911.08962","snapshot_observed_at":"2026-08-05T11:48:52.954898Z","title":"CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain","venue":"cs.CL","work_id":"82225c5b-c7f1-4347-9063-ba42245e7918","year":2019},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.327530Z"},"links":{"cited_paper":"/paper/1911.08962","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:07f7c5edc263771f28c7d36f7cd77f876a40cdd551d4bf90f405b03feb54a26d","observation_id":"73914885-9805-4acd-9866-017acec9815d","resolution":{"observed_at":"2026-08-05T11:48:53.046467Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:54.642236Z","title":"British Journal of Educational Technology55(1), 90–112 (2024)","venue":null,"work_id":"a22bd4da-17ff-4f58-8809-870abe079739","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.380584Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:6b20c8167cd0ed35125b13860f1c6f842fd29b7806ac917ac25b2a2782286cdb","observation_id":"e998665d-b46e-42e7-a69c-f8042e60a49a","resolution":{"observed_at":"2026-08-05T11:48:54.714683Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2306.13549","last_updated":"2024-11-29T15:51:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-06-23T15:21:52Z","title":"A Survey on Multimodal Large Language Models","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2306.13549","snapshot_observed_at":"2026-08-05T11:48:51.432571Z","title":"arXiv preprint arXiv:2306.13549 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.432571Z"},"links":{"cited_paper":"/paper/2306.13549","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:6885291d838bb23626ba879305734ea16b6e2abed3595a780766ba180882f910","observation_id":"3c48cc10-d1ae-42e6-9dee-ba5103593021","resolution":{"observed_at":"2026-08-05T11:48:51.432571Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14531","last_updated":"2024-10-14T12:34:55Z","snapshot_observed_at":"2026-08-09T05:53:27.246349Z","submitted_at":"2024-02-22T13:24:10Z","title":"Should We Respect LLMs? A Cross-Lingual Study on the Influence of Prompt Politeness on LLM Performance","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14531","snapshot_observed_at":"2026-08-05T11:48:51.487133Z","title":"arXiv preprint arXiv:2402.14531 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.487133Z"},"links":{"cited_paper":"/paper/2402.14531","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:fb6f37c3bf10c59f05b7db6762ed016cc70f4da511f74db7eb1816d2d3177d0e","observation_id":"d16341e6-f316-448d-a9c8-5ef4e6b6c858","resolution":{"observed_at":"2026-08-05T11:48:51.487133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.01326","last_updated":"2022-12-08T22:28:10Z","snapshot_observed_at":"2026-07-06T14:26:13.635588Z","submitted_at":"2022-12-02T17:41:22Z","title":"Legal Prompting: Teaching a Language Model to Think Like a Lawyer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.01326","snapshot_observed_at":"2026-08-05T11:48:51.591055Z","title":"arXiv preprint arXiv:2212.01326 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.591055Z"},"links":{"cited_paper":"/paper/2212.01326","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:4419e98f4df6c65bbb0381886a7d7cda7704294a54f585e3ba5bf58027a98779","observation_id":"0528b318-de0b-40af-ac69-a5464667b8cf","resolution":{"observed_at":"2026-08-05T11:48:51.591055Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13601","last_updated":"2024-05-28T05:36:23Z","snapshot_observed_at":"2026-08-09T14:50:09.702964Z","submitted_at":"2024-01-24T17:10:45Z","title":"MM-LLMs: Recent Advances in MultiModal Large Language Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13601","snapshot_observed_at":"2026-08-05T11:48:51.663360Z","title":"arXiv preprint arXiv:2401.13601 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.663360Z"},"links":{"cited_paper":"/paper/2401.13601","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:90b154c4c0e7648666acd43bfc7184feb65eaac27cbc36125592145f7c2690f8","observation_id":"5da4d409-f650-46a5-a006-ecd48dd841e1","resolution":{"observed_at":"2026-08-05T11:48:51.663360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14556","last_updated":"2025-02-22T03:58:03Z","snapshot_observed_at":"2026-07-06T20:09:47.427018Z","submitted_at":"2024-12-19T06:14:20Z","title":"CitaLaw: Enhancing LLM with Citations in Legal Domain","version":2},"cited_work":{"arxiv_id":"2412.14556","doi":null,"metadata_source":"pith","pith_arxiv_id":"2412.14556","snapshot_observed_at":"2026-08-05T11:48:52.697336Z","title":"CitaLaw: Enhancing LLM with Citations in Legal Domain","venue":"cs.CL","work_id":"a5f1540c-6b51-44c9-b539-10d743615912","year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.735994Z"},"links":{"cited_paper":"/paper/2412.14556","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:b4c31a7944a50d803f67eb76c001eba036181663449016370e50ffa88a915690","observation_id":"d587dc58-e5e7-444f-abc7-51216360f881","resolution":{"observed_at":"2026-08-05T11:48:52.795319Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T11:48:54.523600Z","title":"Transactions of the Association for Computational Linguistics 11, 1114–1131 (2023) 20 Klem et al","venue":null,"work_id":"8a393191-f944-4645-9b7b-ef114fae1275","year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.815449Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:b33a0f99c2ef147111c0890dadbb10b05f2886669ac437e8ad3c53efcb41297f","observation_id":"91b830ba-8187-4faa-b9d4-a831eeb9dbda","resolution":{"observed_at":"2026-08-05T11:48:54.581992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03493","last_updated":"2022-10-07T12:28:21Z","snapshot_observed_at":"2026-07-06T14:01:50.333970Z","submitted_at":"2022-10-07T12:28:21Z","title":"Automatic Chain of Thought Prompting in Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03493","snapshot_observed_at":"2026-08-05T11:48:51.875784Z","title":"arXiv preprint arXiv:2210.03493 (2022)","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.875784Z"},"links":{"cited_paper":"/paper/2210.03493","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:6e68a7ee12d5acfdf32fb6888c0234641fe8d0d5405d5d3f343238bab095bd4b","observation_id":"ef91febe-48de-4b92-9ef7-1d28933c4e3f","resolution":{"observed_at":"2026-08-05T11:48:51.875784Z","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":"2026-08-05T11:48:51.930619Z","title":"arXiv preprint arXiv:2401.11641 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.930619Z"},"links":{"citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:41435f71ef59e3518ef8dca9979dcaadc7ff78834804c5e97d18016d3e41f89e","observation_id":"098fd411-ea29-471a-8b2a-8fe5689ac38b","resolution":{"observed_at":"2026-08-05T11:48:51.930619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.02046","last_updated":"2024-04-29T09:06:51Z","snapshot_observed_at":"2026-08-07T00:54:27.770577Z","submitted_at":"2023-07-05T06:03:40Z","title":"Recommender Systems in the Era of Large Language Models (LLMs)","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.02046","snapshot_observed_at":"2026-08-05T11:48:51.987929Z","title":"arXiv preprint arXiv:2307.02046 (2023)","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:51.987929Z"},"links":{"cited_paper":"/paper/2307.02046","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:5e4d9c1c973d0306f4cde7020a07cd439e37b5f0d32cecc2520276d780cd86c6","observation_id":"d0672fd7-6dda-4c4b-9728-60078314d14b","resolution":{"observed_at":"2026-08-05T11:48:51.987929Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16038","last_updated":"2024-01-30T14:37:10Z","snapshot_observed_at":"2026-08-06T12:45:18.285554Z","submitted_at":"2024-01-30T14:37:10Z","title":"A Survey on Generative AI and LLM for Video Generation, Understanding, and Streaming","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16038","snapshot_observed_at":"2026-08-05T11:48:52.090201Z","title":"arXiv preprint arXiv:2404.16038 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-05T11:48:52.090201Z"},"links":{"cited_paper":"/paper/2404.16038","citing_paper":"/paper/2509.02241"},"observation_digest":"sha256:3e78a14d4266ad380973debdcba744e300d61a7f1593b5538f1299e6f7737054","observation_id":"c7799bdf-f01b-464d-895e-ed9e837ebc29","resolution":{"observed_at":"2026-08-05T11:48:52.090201Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2509.02241","last_updated":"2025-09-02T12:09:49Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-09T17:42:44.908227Z","submitted_at":"2025-09-02T12:09:49Z","title":"LLMs for LLMs: A Structured Prompting Methodology for Long Legal Documents"},"reference_resolution":{"displayed":83,"state_counts":{"malformed_identifier":0,"metadata_mismatch":8,"parse_uncertain":0,"unresolved":47,"verified_exact":1,"verified_fuzzy":27},"total_outbound_references":83},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 0 inbound Pith citation observations for arXiv:2509.02241."}