{"as_of":"2026-08-07T05:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:497fe9b6f08c50d41dc8ea508820a275641300941d604e47bc2babc8766f5cd6","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:51:56.340360Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.12425/citation-record","integrity":"/paper/2507.12425/integrity","json":"/paper/2507.12425/citation-record.json","paper":"/paper/2507.12425"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2108.07258","last_updated":"2022-07-12T23:45:14Z","snapshot_observed_at":"2026-08-02T09:20:40.804790Z","submitted_at":"2021-08-16T17:50:08Z","title":"On the Opportunities and Risks of Foundation Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.07258","snapshot_observed_at":"2026-08-06T16:51:54.554629Z","title":"Bommasani et al","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:54.554629Z"},"links":{"cited_paper":"/paper/2108.07258","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:815406416561a82473b43de1be986bb431ba6b4d5ae160191660e800412d6eb9","observation_id":"4a50a754-f07a-4efb-bd38-48b86a9d974f","resolution":{"observed_at":"2026-08-06T16:51:54.554629Z","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":"2026-08-06T16:51:57.180743Z","title":"Camelot: PDF Table Extraction for Humans","venue":null,"work_id":"58aa3a79-1cac-478b-aa9c-46330662f875","year":2018},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:54.626707Z"},"links":{"citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:9776ec837d52ce7e8aba186f3656150eb55f2b125405ee59e87e4679b9fcdbe2","observation_id":"58bcb85f-8e67-4414-ad9b-3048db5a08b8","resolution":{"observed_at":"2026-08-06T16:51:57.290635Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.02311","last_updated":"2022-10-05T06:02:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-05T16:11:45Z","title":"PaLM: Scaling Language Modeling with Pathways","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.02311","snapshot_observed_at":"2026-08-06T16:51:54.709081Z","title":"Chowdhery et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:54.709081Z"},"links":{"cited_paper":"/paper/2204.02311","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:34f2ff504cd575d9e86fec412c675a73fd0f4edc2b7832b901aee25435e9b1f3","observation_id":"4d33291f-d523-477f-83b5-bc62baf37625","resolution":{"observed_at":"2026-08-06T16:51:54.709081Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10496","last_updated":"2022-12-20T18:09:52Z","snapshot_observed_at":"2026-07-06T14:33:08.041820Z","submitted_at":"2022-12-20T18:09:52Z","title":"Precise Zero-Shot Dense Retrieval without Relevance Labels","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10496","snapshot_observed_at":"2026-08-06T16:51:54.828394Z","title":"Gao et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:54.828394Z"},"links":{"cited_paper":"/paper/2212.10496","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:b5879c99306e260aa871ec697530ca7c65a2c3f92e0d0f6239c645ad411bee69","observation_id":"83caded3-7bbf-4af8-86f1-6e5064cec011","resolution":{"observed_at":"2026-08-06T16:51:54.828394Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2002.08909","last_updated":"2020-02-10T18:40:59Z","snapshot_observed_at":"2026-08-02T17:52:27.326803Z","submitted_at":"2020-02-10T18:40:59Z","title":"REALM: Retrieval-Augmented Language Model Pre-Training","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2002.08909","snapshot_observed_at":"2026-08-06T16:51:54.914720Z","title":"Guu et al","venue":null,"work_id":null,"year":2002},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:54.914720Z"},"links":{"cited_paper":"/paper/2002.08909","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:dbfd4eef5a56b6ee661001e12f95137aa0185854de66ef54b14ac7b0056ec270","observation_id":"4a2982a0-c041-4437-815d-9ab485f12109","resolution":{"observed_at":"2026-08-06T16:51:54.914720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.02349","last_updated":"2020-04-21T15:09:48Z","snapshot_observed_at":"2026-08-04T23:31:44.274839Z","submitted_at":"2020-04-05T23:18:37Z","title":"TAPAS: Weakly Supervised Table Parsing via Pre-training","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.02349","snapshot_observed_at":"2026-08-06T16:51:55.034701Z","title":"Herzig et al","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.034701Z"},"links":{"cited_paper":"/paper/2004.02349","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:b2630fe10aa8af2e53f5ed5479b97dde41a8d03783e3e8cf60822a29307879b7","observation_id":"90f874fd-0797-42b5-8f4c-442d6bdef2cf","resolution":{"observed_at":"2026-08-06T16:51:55.034701Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2007.01282","last_updated":"2021-02-03T09:18:34Z","snapshot_observed_at":"2026-08-03T22:53:08.799163Z","submitted_at":"2020-07-02T17:44:57Z","title":"Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2007.01282","snapshot_observed_at":"2026-08-06T16:51:55.127079Z","title":"Izacard and E","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.127079Z"},"links":{"cited_paper":"/paper/2007.01282","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:cc7a823413e9f0bb10b4d6382bfacb3d1e7c226f6702725530aa63f5e4fc1646","observation_id":"963e1bde-9d0e-423b-8306-76cdbfff8035","resolution":{"observed_at":"2026-08-06T16:51:55.127079Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.04906","last_updated":"2020-09-30T21:27:13Z","snapshot_observed_at":"2026-07-06T09:11:26.109763Z","submitted_at":"2020-04-10T04:53:17Z","title":"Dense Passage Retrieval for Open-Domain Question Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.04906","snapshot_observed_at":"2026-08-06T16:51:55.218679Z","title":"Karpukhin et al","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.218679Z"},"links":{"cited_paper":"/paper/2004.04906","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:cd64f2ae8b278acd210d2d8abb94a936374a73d8dcbf7c421f703e2cb5da1171","observation_id":"a0dd0afd-c68c-4849-b030-5293374ad000","resolution":{"observed_at":"2026-08-06T16:51:55.218679Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2005.11401","last_updated":"2021-04-12T15:42:18Z","snapshot_observed_at":"2026-08-04T13:06:14.768886Z","submitted_at":"2020-05-22T21:34:34Z","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11401","snapshot_observed_at":"2026-08-06T16:51:55.295309Z","title":"Lewis et al","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.295309Z"},"links":{"cited_paper":"/paper/2005.11401","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:6d8a01f1325085d08e6f2f23a9816048e659cf2c0dd1e29fdf4cebe143b538f3","observation_id":"639c193e-40de-4ebd-a2c1-f56ebb21d722","resolution":{"observed_at":"2026-08-06T16:51:55.295309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1901.04085","last_updated":"2020-04-14T14:57:40Z","snapshot_observed_at":"2026-08-02T11:18:37.014004Z","submitted_at":"2019-01-13T23:27:58Z","title":"Passage Re-ranking with BERT","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1901.04085","snapshot_observed_at":"2026-08-06T16:51:55.359586Z","title":"Nogueira and K","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.359586Z"},"links":{"cited_paper":"/paper/1901.04085","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:c1d03d21b97327fbfec292d9aa7afd2458e0c5ccc67d6ccb3f0b7b21a35c7a02","observation_id":"ca763828-ddb3-4556-9d9e-02d67dbf9dd4","resolution":{"observed_at":"2026-08-06T16:51:55.359586Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-06T16:51:55.395998Z","title":"GPT-4 Technical Report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.395998Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:974ea0d8c9da2c6115015797faeded3b944479d2f6b6691a751b31147671c7fb","observation_id":"18546d44-131f-4f4c-800c-e22b8f679efd","resolution":{"observed_at":"2026-08-06T16:51:55.395998Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.07511","last_updated":"2021-08-04T13:52:03Z","snapshot_observed_at":"2026-08-05T20:06:44.504455Z","submitted_at":"2021-04-15T15:09:32Z","title":"Ensemble of MRR and NDCG models for Visual Dialog","version":3},"cited_work":{"arxiv_id":"2104.07511","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.07511","snapshot_observed_at":"2026-08-06T16:51:56.518214Z","title":"Ensemble of MRR and NDCG models for Visual Dialog","venue":"cs.AI","work_id":"778c1155-4261-4e41-9053-5564885c6092","year":2021},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.479624Z"},"links":{"cited_paper":"/paper/2104.07511","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:d48a117f5ec5fbd4114513799ca8f507104f9078cd9a1f9ebcba438af898759d","observation_id":"de302584-657b-4b03-b190-fa2ba2b8741c","resolution":{"observed_at":"2026-08-06T16:51:56.537768Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2108.12409","last_updated":"2022-04-22T18:20:48Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2021-08-27T17:35:06Z","title":"Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2108.12409","snapshot_observed_at":"2026-08-06T16:51:55.590706Z","title":"Press et al","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.590706Z"},"links":{"cited_paper":"/paper/2108.12409","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:6796f8495dfa4bb55671b077c81aa2ad43b61b0a5aad1b87658813a9a8531516","observation_id":"24d6a46a-10b0-4296-986f-c98f6911c08f","resolution":{"observed_at":"2026-08-06T16:51:55.590706Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10084","last_updated":"2019-08-27T08:50:17Z","snapshot_observed_at":"2026-07-06T08:17:05.681370Z","submitted_at":"2019-08-27T08:50:17Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10084","snapshot_observed_at":"2026-08-06T16:51:55.685709Z","title":"Reimers and I","venue":null,"work_id":null,"year":1908},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.685709Z"},"links":{"cited_paper":"/paper/1908.10084","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:98d89f4ab73c0e26834603971e19472d82db6914425a6d17bee54f6658516e85","observation_id":"52c5e50c-dcb4-4e49-8f21-9696f7791ae5","resolution":{"observed_at":"2026-08-06T16:51:55.685709Z","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":"2026-08-06T16:51:56.876489Z","title":"Robertson and H","venue":null,"work_id":"ef0245c9-51f6-4d28-ba15-4e52bdcf0a85","year":2009},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.763188Z"},"links":{"citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:ea5af91d29a8a9a9a9cc8388911befbe2635c143c40e11569b11b326d80636c1","observation_id":"1d50bdcd-76f0-4fc4-a9ae-125571deb0b3","resolution":{"observed_at":"2026-08-06T16:51:57.049797Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.11366","last_updated":"2023-10-10T05:21:45Z","snapshot_observed_at":"2026-07-06T15:05:53.556198Z","submitted_at":"2023-03-20T18:08:50Z","title":"Reflexion: Language Agents with Verbal Reinforcement Learning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.11366","snapshot_observed_at":"2026-08-06T16:51:55.838603Z","title":"Shinn et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.838603Z"},"links":{"cited_paper":"/paper/2303.11366","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:59af3038abd6dbae559764b4407f6cdf2dc069ad89cdadd837a2f5fe58fa94b9","observation_id":"082284b8-01ee-418a-9c47-b53966abb90e","resolution":{"observed_at":"2026-08-06T16:51:55.838603Z","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":"2026-08-06T16:51:56.659171Z","title":"spaCy: Industrial-Strength Natural Language Processing","venue":null,"work_id":"a46ca399-1db0-429b-9440-ead66c61336f","year":2020},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.888536Z"},"links":{"citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:41bb1606d14746e3a417ff85006a767433a68412f7f3fb807c3a4f8db6bea7a4","observation_id":"1e67dbc6-cd93-46bf-807a-f18329c29e76","resolution":{"observed_at":"2026-08-06T16:51:56.749658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.13971","last_updated":"2023-02-27T17:11:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-02-27T17:11:15Z","title":"LLaMA: Open and Efficient Foundation Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.13971","snapshot_observed_at":"2026-08-06T16:51:55.979590Z","title":"Touvron et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:55.979590Z"},"links":{"cited_paper":"/paper/2302.13971","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:538ce74fae80888d02fd8a24631f7f45067637baa611820da46a6b158c725568","observation_id":"11f9f7f6-3ea9-44f1-a65c-96dfd6e9a0c9","resolution":{"observed_at":"2026-08-06T16:51:55.979590Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.03629","last_updated":"2023-03-10T01:00:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-10-06T01:00:32Z","title":"ReAct: Synergizing Reasoning and Acting in Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.03629","snapshot_observed_at":"2026-08-06T16:51:56.079892Z","title":"Yao et al","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:56.079892Z"},"links":{"cited_paper":"/paper/2210.03629","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:7954dfee1937037803df4ddd8f02fc06d2bf573bbe2d7674ae3dfc4e572ff3bb","observation_id":"82c1a694-5bcd-467d-af74-2018a87a2c15","resolution":{"observed_at":"2026-08-06T16:51:56.079892Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2006.14806","last_updated":"2020-12-03T02:47:41Z","snapshot_observed_at":"2026-08-05T22:33:22.075883Z","submitted_at":"2020-06-26T05:44:54Z","title":"TURL: Table Understanding through Representation Learning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2006.14806","snapshot_observed_at":"2026-08-06T16:51:56.162436Z","title":"Zhang et al","venue":null,"work_id":null,"year":2006},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:56.162436Z"},"links":{"cited_paper":"/paper/2006.14806","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:6eab1d1a4c20d36a95700ee488e91e686d6abba07d8cf98e9a5457de10721ade","observation_id":"ef467f1a-6e04-4737-891d-deb5eaae908a","resolution":{"observed_at":"2026-08-06T16:51:56.162436Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.07842","last_updated":"2023-02-15T18:25:52Z","snapshot_observed_at":"2026-07-30T02:11:00.198428Z","submitted_at":"2023-02-15T18:25:52Z","title":"Augmented Language Models: a Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.07842","snapshot_observed_at":"2026-08-06T16:51:56.243044Z","title":"Mialon et al","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:56.243044Z"},"links":{"cited_paper":"/paper/2302.07842","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:f9bdb540ce91243cf3edf76565182e519769d4f2143c21b9fdcecc7bff8d901c","observation_id":"c51d580f-deaf-4432-9376-bd07e563f21a","resolution":{"observed_at":"2026-08-06T16:51:56.243044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.12832","last_updated":"2020-06-04T05:28:21Z","snapshot_observed_at":"2026-08-04T09:38:32.896372Z","submitted_at":"2020-04-27T14:21:03Z","title":"ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.12832","snapshot_observed_at":"2026-08-06T16:51:56.340360Z","title":"Khattab and M","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:51:56.340360Z"},"links":{"cited_paper":"/paper/2004.12832","citing_paper":"/paper/2507.12425"},"observation_digest":"sha256:4708538c005a4e658519014c916a1a20dcacb3220c3ce6f03c4e1a638a95c50d","observation_id":"b0d0f173-d2a1-4a3c-9e44-81455c679471","resolution":{"observed_at":"2026-08-06T16:51:56.340360Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.12425","last_updated":"2025-07-16T17:13:06Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-06T16:43:38.785449Z","submitted_at":"2025-07-16T17:13:06Z","title":"Advancing Retrieval-Augmented Generation for Structured Enterprise and Internal Data"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":18,"verified_exact":1,"verified_fuzzy":3},"total_outbound_references":22},"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":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:2507.12425."}