{"as_of":"2026-08-17T15:53:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e38f385397c1f6cd9cd20ee73351c053f0d0d4a616d4405c6e9303d31183eaf0","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:25:18.112045Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-17T06:30:58.91139+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/2608.13384/citation-record","integrity":"/paper/2608.13384/integrity","json":"/paper/2608.13384/citation-record.json","paper":"/paper/2608.13384"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:19.347300Z","title":"80 Percent of Your Data Will Be Unstructured in Five Years,","venue":null,"work_id":"08736736-8bd9-4d41-8e75-4b3adc9f640d","year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.851619Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:c038d49b3bf128d6bfeca02b809b0c18cc045c392855d26c97a48a781329c97e","observation_id":"fbee80ec-00be-4720-856c-eb7807cf4191","resolution":{"observed_at":"2026-08-14T12:25:19.353473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.328119Z","title":"Simplifying data integration: Slm-driven systems for unified semantic queries across heterogeneous databases,","venue":null,"work_id":"d80386b2-c9d9-4986-bddd-e5c6e049f0fd","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.858417Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:4c8d4dfd3a76c9f75d1e79c12a74326ac5c95ad433e53469bc0051a9e6218fc7","observation_id":"e10a1a0c-30e6-430f-9e16-306255f133ba","resolution":{"observed_at":"2026-08-14T12:25:19.334137Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.309521Z","title":"MEBench: Benchmarking large language models for cross-document multi-entity question answering,","venue":null,"work_id":"76a90899-1c5f-4daf-96a0-a64870fbd2a8","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.864438Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:64e6cd14af8b9453a9812853a515caed0ec6864ccbef60b2357961b283b1ee15","observation_id":"1bd7ac9f-3f39-43da-878d-584d075b2ba1","resolution":{"observed_at":"2026-08-14T12:25:19.315639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.287847Z","title":"Palimpzest: Optimizing ai-powered analytics with declarative query processing,","venue":null,"work_id":"31c2872f-d9a6-46f8-b268-0a7bce20262f","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.870529Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:0b6eb389536b4658664de8cda1d9c9e1dedc04d43795ec51e8fff950d6f75ae4","observation_id":"ed116d46-8b75-4f08-a9cc-0b6a873e80e2","resolution":{"observed_at":"2026-08-14T12:25:19.294070Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.258872Z","title":"Querying templatized document collections with large language models,","venue":null,"work_id":"99db3a7e-218b-466c-ace7-8905f8af8ecd","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.878066Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:694e0c5db724e43481beaa60aa3abf9eea6eaf5acc0990b337befde229088ff2","observation_id":"128cfef6-3bcb-4fd0-9b27-2b18b697268b","resolution":{"observed_at":"2026-08-14T12:25:19.265123Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.235359Z","title":"Quest: Query optimization in unstructured document analysis,","venue":null,"work_id":"66ea21d4-91e3-43e5-8149-21ce3516dd1e","year":null},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.885351Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:b56f7802d87248b24747878eb7f491d6bc4f113754147766a9d82b6b793b774f","observation_id":"0ff009d1-3cdf-4f6d-bebe-666ddf650543","resolution":{"observed_at":"2026-08-14T12:25:19.241347Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2608.04071","last_updated":"2026-08-04T15:52:05Z","snapshot_observed_at":"2026-08-16T23:05:05.011923Z","submitted_at":"2026-08-04T15:52:05Z","title":"Monte Carlo Tree Search for Table-to-Multimodal Report Generation","version":1},"cited_work":{"arxiv_id":"2608.04071","doi":null,"metadata_source":"pith","pith_arxiv_id":"2608.04071","snapshot_observed_at":"2026-08-14T12:25:18.833207Z","title":"Monte Carlo Tree Search for Table-to-Multimodal Report Generation","venue":"cs.AI","work_id":"b336208d-2403-4493-9176-27580765c19c","year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.901772Z"},"links":{"cited_paper":"/paper/2608.04071","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:c7f7c5c3cada3cf5899564e543adf5d10d5e1bd08a0d1ac7ad6556779c7a9f70","observation_id":"0aac4dcc-e112-4401-abee-757bcc45f770","resolution":{"observed_at":"2026-08-14T12:25:18.838997Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2604.02690","last_updated":"2026-07-19T16:55:28Z","snapshot_observed_at":"2026-08-12T19:57:20.192637Z","submitted_at":"2026-04-03T03:34:19Z","title":"AnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis","version":2},"cited_work":{"arxiv_id":"2604.02690","doi":null,"metadata_source":"pith","pith_arxiv_id":"2604.02690","snapshot_observed_at":"2026-08-14T12:25:18.806425Z","title":"AnnoRetrieve: Efficient Structured Retrieval for Unstructured Document Analysis","venue":"cs.IR","work_id":"a0e473c2-4595-4428-b675-ca3c46213d94","year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.908876Z"},"links":{"cited_paper":"/paper/2604.02690","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:afc883ea2d75ad8d834edbb88efbd90f90a99f4672247df6e2098cfa1372a7d0","observation_id":"febb1d79-8291-483d-a77b-891ab7236b57","resolution":{"observed_at":"2026-08-14T12:25:18.813031Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.216212Z","title":"A survey on rag meeting llms: Towards retrieval-augmented large language models,","venue":null,"work_id":"6b2d9149-fe9b-4410-b3bd-c506c947eb75","year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.915037Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:0b9bc03352d8cd1b953ba26e75a8ca1965e60db7d22b1dadc8331236f573a453","observation_id":"3fa3689a-88bb-4df7-b3eb-706fd9bf54a9","resolution":{"observed_at":"2026-08-14T12:25:19.222307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:17.921627Z","title":"A comprehensive survey on long context language modeling,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.921627Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:622e3b3729e9dcd16ee9ff000821f05db9684615c34da3ddcb7c9138ff22468d","observation_id":"703c8905-9026-434b-b22d-16ea29cf8f28","resolution":{"observed_at":"2026-08-14T12:25:17.921627Z","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":"2026-08-14T12:25:17.927928Z","title":"Docsage: An information structuring agent for multi-doc multi-entity question answering,","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.927928Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:2c0749ae3aff5620bf4ed53a8d77f63cac27106b795cdd65514e340e451ecbc5","observation_id":"92ee903d-ca22-415b-afdf-e4858f878bca","resolution":{"observed_at":"2026-08-14T12:25:17.927928Z","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":"2026-08-14T12:25:19.193070Z","title":"Numerical constraint-aware dense retrieval with two-phase contrastive learning,","venue":null,"work_id":"0a02e6ca-7a9b-4cd4-9a81-5d13642f85d8","year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.932977Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:c32e8c91a5381f3c77088cea7d48d7af6d9ba6a646faf1ccd6520d3b838c6818","observation_id":"3dc68bbd-e226-44f7-8279-eebdb70ac331","resolution":{"observed_at":"2026-08-14T12:25:19.200146Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:17.939544Z","title":"Retrieval- augmented generation for knowledge-intensive nlp tasks,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.939544Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:ab5ea057c10bff33664e2dc03b34af19a836e8b48edd5ca20a8edff861652718","observation_id":"fcf61dfc-281d-48ce-9a62-901b91b4076c","resolution":{"observed_at":"2026-08-14T12:25:17.939544Z","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":"2026-08-14T12:25:19.157068Z","title":"Leave no document behind: Benchmarking long-context LLMs with extended multi-doc QA,","venue":null,"work_id":"23772e3a-bb39-401c-bbce-abcf15123804","year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.946538Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:2327a1a0b92becbd425fedcebcce8be49c8e7d1fa44c341fecec680f6b1424d2","observation_id":"e5f7dd75-ecfe-40ff-b4b6-dbd1d03cc03f","resolution":{"observed_at":"2026-08-14T12:25:19.162408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.139899Z","title":"Structured retrieval-augmented generation for multi-entity question answering over heterogeneous sources,","venue":null,"work_id":"50de77e3-576a-4575-a852-cac91bafe64e","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.951484Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:b0b96a59373040f4efa107b04b4c48e4461a8e64f2ab279a7b3666551ac85a7a","observation_id":"78459ddc-8db3-4b4e-81f8-c7f77192ab7d","resolution":{"observed_at":"2026-08-14T12:25:19.145582Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.00610","last_updated":"2024-03-31T08:58:54Z","snapshot_observed_at":"2026-08-16T14:04:53.635805Z","submitted_at":"2024-03-31T08:58:54Z","title":"RQ-RAG: Learning to Refine Queries for Retrieval Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.00610","snapshot_observed_at":"2026-08-14T12:25:17.958316Z","title":"Rq-rag: Learning to refine queries for retrieval augmented generation,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.958316Z"},"links":{"cited_paper":"/paper/2404.00610","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:4c0d610645c5d7670373e0cf891e30d9b80052b187f8ed6696961fa21b477d1f","observation_id":"9402ef4a-0046-4f13-abe5-b14a3b411aea","resolution":{"observed_at":"2026-08-14T12:25:17.958316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.15294","last_updated":"2023-10-23T09:58:13Z","snapshot_observed_at":"2026-08-16T15:30:05.158869Z","submitted_at":"2023-05-24T16:17:36Z","title":"Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.15294","snapshot_observed_at":"2026-08-14T12:25:17.964085Z","title":"Enhancing retrieval-augmented large language models with iterative retrieval-generation synergy,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.964085Z"},"links":{"cited_paper":"/paper/2305.15294","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:73c7a0fdf073ef27d585f84515da6fe12a4cba7e4069b29d8d73a8e9f64a9e59","observation_id":"c608768e-d442-4cd0-80e2-f32c6f54e66c","resolution":{"observed_at":"2026-08-14T12:25:17.964085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.16130","last_updated":"2025-02-19T10:49:41Z","snapshot_observed_at":"2026-08-16T12:38:40.131901Z","submitted_at":"2024-04-24T18:38:11Z","title":"From Local to Global: A Graph RAG Approach to Query-Focused Summarization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.16130","snapshot_observed_at":"2026-08-14T12:25:17.971096Z","title":"From local to global: A graph rag approach to query- focused summarization,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.971096Z"},"links":{"cited_paper":"/paper/2404.16130","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:61749a8d2a7ab511798b15a4fec9a832905bff4de4968dd03d9686d43f084cf6","observation_id":"273a73e4-8a24-4cc4-b661-9449b233b7e4","resolution":{"observed_at":"2026-08-14T12:25:17.971096Z","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":"2026-08-14T12:25:17.976860Z","title":"Lightkgg: Simple and efficient knowledge graph generation from textual data,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.976860Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:0389f9e131c8707bbba0443d1123e396ba222664b789960e2f2a8eaa607458a7","observation_id":"1128b25f-7e0e-4133-bbeb-ad561175cd46","resolution":{"observed_at":"2026-08-14T12:25:17.976860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.01346","last_updated":"2025-03-06T12:27:24Z","snapshot_observed_at":"2026-08-16T12:53:40.471597Z","submitted_at":"2025-03-03T09:37:33Z","title":"SRAG: Structured Retrieval-Augmented Generation for Multi-Entity Question Answering over Wikipedia Graph","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.01346","snapshot_observed_at":"2026-08-14T12:25:17.985818Z","title":"Srag: Structured retrieval- augmented generation for multi-entity question answering over wikipedia graph,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.985818Z"},"links":{"cited_paper":"/paper/2503.01346","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:ea979663d89807a68633aff5b4f7e3351c4d4bf98c0324131fbf89d7ff65ee86","observation_id":"24b38a5c-ea6e-4099-9e41-4eaf0a275cc9","resolution":{"observed_at":"2026-08-14T12:25:17.985818Z","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":"2026-08-14T12:25:19.122446Z","title":"deepdoctection,","venue":null,"work_id":"18def1fc-bfcc-4a10-82b2-4ee7749d73d2","year":2023},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.993450Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:91699dccaa91d80dc7a729cbc9db2011a9ba76296945af137d61e41a6b87e491","observation_id":"e53f0f72-e6a0-4189-82b7-fa198ed1faaf","resolution":{"observed_at":"2026-08-14T12:25:19.128194Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.12189","last_updated":"2025-04-01T19:47:19Z","snapshot_observed_at":"2026-08-16T13:08:58.241198Z","submitted_at":"2024-10-16T03:22:35Z","title":"DocETL: Agentic Query Rewriting and Evaluation for Complex Document Processing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.12189","snapshot_observed_at":"2026-08-14T12:25:17.998474Z","title":"Docetl: Agentic query rewriting and evaluation for complex document processing,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.998474Z"},"links":{"cited_paper":"/paper/2410.12189","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:1229330046919221ededc97d67e40751de1748e207455d7f7f58be9fffb90d4d","observation_id":"4739de44-77d7-431d-a2df-c1120054d242","resolution":{"observed_at":"2026-08-14T12:25:17.998474Z","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":"2026-08-14T12:25:19.105827Z","title":"Unstructured,","venue":null,"work_id":"3af04736-9fcd-4159-bcb1-fcb212351a02","year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.003893Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:41aa1cca6f9ba1c4ef5e928279278217398ea4af75401b515f26caa792c907da","observation_id":"d1fe2d37-9b9e-4b21-98f7-5ad9d022c66e","resolution":{"observed_at":"2026-08-14T12:25:19.111167Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:18.009331Z","title":"Retrieval-augmented generation for large language models: A survey,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.009331Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:0b43aea94bf8a9eb61d53a4c5f6fe2770c9a70a9d6d3b791da72497701d55b7d","observation_id":"ba4a837a-4ca0-4592-b3fc-58f5c6134a0e","resolution":{"observed_at":"2026-08-14T12:25:18.009331Z","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":"2026-08-14T12:25:19.087277Z","title":"Doctopus: Budget-aware structural table extraction from unstructured documents,","venue":null,"work_id":"e71cf71c-5712-48c6-aebc-449ed1223ade","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.015733Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:6c299f95753c692caf10b7bfd6093caa13b3ea90daa0ae95a01751b555b1eb93","observation_id":"599a0d8e-98d5-4d75-94fb-80b6a3901901","resolution":{"observed_at":"2026-08-14T12:25:19.093148Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.063663Z","title":"Docdb: A database for unstructured document analysis,","venue":null,"work_id":"72fc6342-6ec0-490d-8fd2-9dabc1ad98f7","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.021453Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:b9bffeea2129c93075cb65fbc8f54bb130ccd7d71162a93c9aba99b26b70fa29","observation_id":"d80ca525-ed80-4422-8677-b886af9bc772","resolution":{"observed_at":"2026-08-14T12:25:19.069809Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.038057Z","title":"Eleet: Efficient learned query execution over text and tables,","venue":null,"work_id":"63a2bc45-bea7-4109-81ce-49e834652105","year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.028856Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:89ffd60075a02935e44af5d3bb9ab116e6ef19050a74789ded3ab9ba79841404","observation_id":"b06e394c-4035-421f-bfef-8cbbbf8308f7","resolution":{"observed_at":"2026-08-14T12:25:19.046823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:19.019514Z","title":"Unify: A system for unstructured data analytics,","venue":null,"work_id":"0e936c91-e2c2-4512-9cb5-6f806d6f6264","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.036547Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:f185dc8fa9c0efda457f458e43178bd106507deb1e63dc82d16a6a837d476759","observation_id":"f9d38f94-80f3-41d9-8825-f0215dbe9041","resolution":{"observed_at":"2026-08-14T12:25:19.025646Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:18.045084Z","title":"Acorn: Performant and predicate-agnostic search over vector embeddings and structured data,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.045084Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:277f18738d84b9aec086f546c56b1804b1a90bd8779781c591b75bf09500f3b1","observation_id":"aab609df-3363-46f7-bdb1-186e355bba64","resolution":{"observed_at":"2026-08-14T12:25:18.045084Z","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":"2509.19757","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:25:18.484275Z","title":"Arcade: A real-time data system for hybrid and continuous query processing across diverse data modalities,","venue":null,"work_id":"7eb12136-69ce-4d78-b959-06dee1c8fef7","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.050747Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:def84fe5570911295811a60ee788f83afb2d6c8e41e548fff124d499fc903ff1","observation_id":"cd699e9e-f106-44b9-9c57-096335ff6a86","resolution":{"observed_at":"2026-08-14T12:25:18.495537Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.23628","last_updated":"2025-08-01T06:39:45Z","snapshot_observed_at":"2026-08-14T18:56:29.304736Z","submitted_at":"2025-05-29T16:34:58Z","title":"AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.23628","snapshot_observed_at":"2026-08-14T12:25:18.056903Z","title":"Autoschemakg: Autonomous knowledge graph construction through dynamic schema induction from web-scale corpora,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.056903Z"},"links":{"cited_paper":"/paper/2505.23628","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:5994eb82b3094bb1afadaff95c511608aef25d6ab6d073998d1e45330678384c","observation_id":"d9b50095-cfab-447b-8f83-91f89c16778f","resolution":{"observed_at":"2026-08-14T12:25:18.056903Z","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":"2026-08-14T12:25:18.999465Z","title":"SQUiD: Synthesizing relational databases from unstructured text,","venue":null,"work_id":"984d5d06-c42c-4d4f-9f72-08ffc7956510","year":2025},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.062865Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:c2fa427004dc77a245842bfe6ed1bc08d2022e5f92c9df59164c724b75d62ee0","observation_id":"deeabeb7-5080-48dc-a5ac-2ded86996116","resolution":{"observed_at":"2026-08-14T12:25:19.005829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:18.981274Z","title":"Lexa: Towards automatic legal citation classification,","venue":null,"work_id":"a9d10164-bed2-4ad6-9455-c3a1883d5168","year":2010},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.068605Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:2f269b23f7e624fc375c2d33a17a3031bbe3655d2774b813fb4f9a72c8feb559","observation_id":"9e9915e9-92d0-4a9d-8789-c414edbc3c0b","resolution":{"observed_at":"2026-08-14T12:25:18.986868Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:18.074666Z","title":"From one tree to a forest: a unified solution for structured web data extraction,","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.074666Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:192f60f08c1e779654d778c2e7d2a4894ac431c5d7248fee0519e88003364ff8","observation_id":"fab978b5-a019-45fe-82ca-51d7530ca619","resolution":{"observed_at":"2026-08-14T12:25:18.074666Z","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":"2026-08-14T12:25:18.960106Z","title":"Vectordb: A minimal python package for storing and retrieving text using chunking, embeddings, and vector search,","venue":null,"work_id":"cc3af73d-df6b-4ae0-9b8d-0622e3a5bf6e","year":2026},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.081525Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:7e21013b916547a23f509c71f952c16e3c76eab145dc2e5f3522a44ed8df34b8","observation_id":"49139aff-c6bd-492a-9671-0703c1888223","resolution":{"observed_at":"2026-08-14T12:25:18.966154Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+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":"2026-08-14T12:25:18.941297Z","title":"Openai embedding model,","venue":null,"work_id":"1885c304-b05c-4026-b9e7-2971eea18098","year":null},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.088621Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:c6332f07455da0aa927ac9e00777f65e59bcaaac0acd0e1c49b5b7acf54e7a05","observation_id":"5d2fe539-45af-4da6-9d59-d28ee4b58528","resolution":{"observed_at":"2026-08-14T12:25:18.947081Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11418","last_updated":"2025-03-01T01:47:51Z","snapshot_observed_at":"2026-08-16T13:33:54.457898Z","submitted_at":"2024-07-16T06:19:14Z","title":"Semantic Operators: A Declarative Model for Rich, AI-based Data Processing","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11418","snapshot_observed_at":"2026-08-14T12:25:18.094372Z","title":"Lotus: Enabling semantic queries with llms over tables of unstructured and structured data,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.094372Z"},"links":{"cited_paper":"/paper/2407.11418","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:8d392758e57822bc0b000f231ac5145ab6f779768f9b56a42ca6cef7a22d3ce0","observation_id":"999da4b2-cdc5-4783-acea-91a1a49c87c4","resolution":{"observed_at":"2026-08-14T12:25:18.094372Z","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":"2026-08-14T12:25:18.923290Z","title":"Deberta: Decoding- enhanced bert with disentangled attention,","venue":null,"work_id":"d5c1c45d-d058-4e55-877c-48bd90aacdea","year":2021},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.100496Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:bf6c935dc4c6a343d68df9a16b78c60012a99cc5b809f3b0cc339fc0e754ba74","observation_id":"1aaf1e59-395e-44c2-97bb-c6d3ea8e226e","resolution":{"observed_at":"2026-08-14T12:25:18.928283Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-17T09:58:46.058102Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-14T12:25:18.106264Z","title":"Gpt-4 technical report,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.106264Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:bfa998727e734fd8e344ab61a11848992e48176ed2465362c451abf906ae37d7","observation_id":"42186148-3776-495d-8059-ff22da91fdd2","resolution":{"observed_at":"2026-08-14T12:25:18.106264Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.06825","last_updated":"2023-10-10T17:54:58Z","snapshot_observed_at":"2026-08-17T02:13:39.510069Z","submitted_at":"2023-10-10T17:54:58Z","title":"Mistral 7B","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.06825","snapshot_observed_at":"2026-08-14T12:25:18.112045Z","title":"Mistral 7b,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:18.112045Z"},"links":{"cited_paper":"/paper/2310.06825","citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:66c223dc5d1b68d9b1005c1b3b4bc59535a30838d85b03998675e43bc51688f7","observation_id":"f5fc2d52-26c4-4b8b-a055-71d3bbe3023e","resolution":{"observed_at":"2026-08-14T12:25:18.112045Z","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":"2026-08-14T12:25:17.892184Z","title":"Available: https://doi.org/10.14778/3749646.3749713","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents","version":1},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-14T12:25:17.892184Z"},"links":{"citing_paper":"/paper/2608.13384"},"observation_digest":"sha256:3caea16dc7c52bb18e9823303075cf9dc5df0ccc3eba517bec8086393e97c979","observation_id":"9d6d98c0-0606-47a8-b1a7-1021a72e1f7c","resolution":{"observed_at":"2026-08-14T12:25:17.892184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.13384","last_updated":"2026-08-13T15:46:20Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-17T13:45:47.828225Z","submitted_at":"2026-08-13T15:46:20Z","title":"Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":3,"verified_fuzzy":21},"total_outbound_references":41},"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":"2026-08-17T06:30:58.91139+00:00","source":"crossref"},{"observed_at":"2026-08-17T06:30:54.323127+00:00","source":"retraction_watch"}],"thesis":"As of 17 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2608.13384."}