{"as_of":"2026-08-14T11:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:685afab74e3f6d9105866b2a94c5c4560b9876b810663bab7e98460b96d0b461","coverage":[{"denominator":171,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-03T17:21:35.117582Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-14T06:32:32.682623+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/2512.11001/citation-record","integrity":"/paper/2512.11001/integrity","json":"/paper/2512.11001/citation-record.json","paper":"/paper/2512.11001"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.04834","last_updated":"2025-07-18T05:02:11Z","snapshot_observed_at":"2026-08-13T00:35:42.679651Z","submitted_at":"2024-04-07T07:05:40Z","title":"LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.04834","snapshot_observed_at":"2026-08-03T17:21:25.840988Z","title":"LLM-Based Multi-Agent Systems for Software Engineering: Literature Review, Vision and the Road Ahead , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:25.840988Z"},"links":{"cited_paper":"/paper/2404.04834","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:287db8ab7a63ee82192f0e8c31564a29227cd177a9e7978ceb118aa295ee4e90","observation_id":"42c1d32c-78e9-4a03-bd16-a135a31aafa7","resolution":{"observed_at":"2026-08-03T17:21:25.840988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2307.04738","last_updated":"2023-07-10T17:52:01Z","snapshot_observed_at":"2026-08-13T10:58:51.030110Z","submitted_at":"2023-07-10T17:52:01Z","title":"RoCo: Dialectic Multi-Robot Collaboration with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2307.04738","snapshot_observed_at":"2026-08-03T17:21:26.006380Z","title":"10.48550/arXiv.2307.04738 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.006380Z"},"links":{"cited_paper":"/paper/2307.04738","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:91bb61667c32ee5ca9ea45bd38dfd2a53c6da36cb9f6e5803b16f175bd028467","observation_id":"2ed1d7ae-5f5d-4f55-ae9b-2eceb6e50b15","resolution":{"observed_at":"2026-08-03T17:21:26.006380Z","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":"2026-08-03T17:21:26.128243Z","title":"The Twelfth International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.128243Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:890f821f58cb9414d78ca949efae87b7758d7b654ad92c327327b3eb22e5956a","observation_id":"36258172-c1e9-4012-95a9-0b1bc318993d","resolution":{"observed_at":"2026-08-03T17:21:26.128243Z","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":"2026-08-03T17:21:26.224922Z","title":"ICML , author=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.224922Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:dd4ee94466c5f5d4d3cc31994af1f6f390bf0e7850fd353ad0c65ce771e30db4","observation_id":"56626ca9-6187-4da0-bcd3-48aa57864a66","resolution":{"observed_at":"2026-08-03T17:21:26.224922Z","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":"2026-08-03T17:21:26.390726Z","title":"IJCAI , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.390726Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:5e4ac4ac9aacdb89b05329445f68954e89e36ea05f5080f6a194a8b756649868","observation_id":"9668657f-5762-4723-812d-53798f1bba4a","resolution":{"observed_at":"2026-08-03T17:21:26.390726Z","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":"2026-08-03T17:21:26.555454Z","title":"NeurIPS , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.555454Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:26054d9b9c8d143a31b2b6d586b7c5b50abbdbeaae2e80d2b46eca5a7bb7bb86","observation_id":"23bdd5fd-6e62-44e1-8a4e-18da4e84e314","resolution":{"observed_at":"2026-08-03T17:21:26.555454Z","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":"2026-08-03T17:21:26.666679Z","title":"Differentiation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.666679Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d214eaa5e22342c66d64dd4a0b594c59bac52700833278fb6f5d0a14f7bbe64d","observation_id":"42e77c4d-781b-4367-8929-37a4bb8d15c5","resolution":{"observed_at":"2026-08-03T17:21:26.666679Z","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":"2026-08-03T17:21:26.784920Z","title":"AutoGen: Enabling Next-Gen","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.784920Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ea6e3bc0401286295e43707dca3a1bb7b3a1a1fd029c0602a2b9e3622b1aa8e3","observation_id":"09007500-e5a2-41aa-a7ae-d88c0e59f0ac","resolution":{"observed_at":"2026-08-03T17:21:26.784920Z","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":"2026-08-03T17:21:26.917055Z","title":"The Berkeley Artificial Intelligence Research Blog , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:26.917055Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d58af823177b00bf8d605741f7d6d43bf22201421d229639c2db42c3f18acd8d","observation_id":"7988a914-4b86-4001-919d-d01ca5aa0d71","resolution":{"observed_at":"2026-08-03T17:21:26.917055Z","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":"2026-08-03T17:21:27.069676Z","title":"Gonzalez and Ion Stoica , booktitle=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.069676Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:4d2b48e72c8b99b7ebbdaa490301c4bc120b9d53c3a58cf544d341dd8782265c","observation_id":"6943abb4-0adc-40e1-9c77-5bef778565bd","resolution":{"observed_at":"2026-08-03T17:21:27.069676Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.12272","last_updated":"2024-04-18T15:45:27Z","snapshot_observed_at":"2026-08-13T00:27:18.458669Z","submitted_at":"2024-04-18T15:45:27Z","title":"Who Validates the Validators? Aligning LLM-Assisted Evaluation of LLM Outputs with Human Preferences","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.12272","snapshot_observed_at":"2026-08-03T17:21:27.143946Z","title":"Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology (UIST) , author=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.143946Z"},"links":{"cited_paper":"/paper/2404.12272","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:401adef907cb6f4c64349bcc24baee18b5b127fa5389703017b64731a68f34cf","observation_id":"2e91dddf-f502-4347-aeba-b63a7138e652","resolution":{"observed_at":"2026-08-03T17:21:27.143946Z","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":"2026-08-03T17:21:27.189329Z","title":"Yan and Haichen Shen and Meghan Cowan and Leyuan Wang and Yuwei Hu and Luis Ceze and Carlos Guestrin and Arvind Krishnamurthy , editor =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.189329Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:67d00554468835bf80c6b71c2996b0fb4a125307b70a53d634f2edc67767d072","observation_id":"ae3f847b-2207-41d1-a206-3b1e42fff870","resolution":{"observed_at":"2026-08-03T17:21:27.189329Z","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":"2026-08-03T17:21:27.327809Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.327809Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:5c6524cc318c94dbf134d82946522f0dc687f514b4cde6478a7f3df9cf87f07f","observation_id":"904c369a-1692-47cc-8eb1-2a903a036eb0","resolution":{"observed_at":"2026-08-03T17:21:27.327809Z","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":"10.1016/j.neucom.2021.04.112","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Neurocomputing , volume =","venue":"Neurocomputing","work_id":"34e4c211-8fb9-4302-a741-13a3a3dc68ee","year":2021},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.430705Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6086aafe6f70695a57684de8df5ae670b0b798e7bcbea46112a6b5d1ad8ab008","observation_id":"7ba87a09-9183-463e-a633-e2e4315d8a76","resolution":{"observed_at":"2026-08-03T17:23:25.033911Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-03T17:21:27.510699Z","title":"ACM Computing Surveys , volume =","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.510699Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:386d981486bb2d21892582dcb8b6356eec74c08859a7092450b002277b98628b","observation_id":"4b2379b2-d558-4b64-ad3e-962b80228104","resolution":{"observed_at":"2026-08-03T17:21:27.510699Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.18182","last_updated":"2025-08-04T15:53:52Z","snapshot_observed_at":"2026-08-11T15:42:15.418166Z","submitted_at":"2025-07-24T08:28:17Z","title":"SCOPE: Stochastic and Counterbiased Option Placement for Evaluating Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.18182","snapshot_observed_at":"2026-08-03T17:21:27.531024Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.531024Z"},"links":{"cited_paper":"/paper/2507.18182","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:1b54f4e054ace29aa5a6d1a4fd02ea9b7941dbbf4ee98e8bde641fb8e92141a4","observation_id":"0c7b0f32-2814-431a-9a24-54afd8f992c0","resolution":{"observed_at":"2026-08-03T17:21:27.531024Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.08053","last_updated":"2025-08-11T14:52:59Z","snapshot_observed_at":"2026-08-13T13:33:11.381344Z","submitted_at":"2025-08-11T14:52:59Z","title":"AdaptFlow: Adaptive Workflow Optimization via Meta-Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.08053","snapshot_observed_at":"2026-08-03T17:21:27.552486Z","title":"arXiv preprint arXiv:2508.08053 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.552486Z"},"links":{"cited_paper":"/paper/2508.08053","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6d9b30d92e797f9f182e0ad5246abef132b69c6b412a6075aba269c7702275ef","observation_id":"6373bcc2-22a9-455a-b5a3-f9f3e9ca7265","resolution":{"observed_at":"2026-08-03T17:21:27.552486Z","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":"2026-08-03T17:21:27.591320Z","title":"Franklin and Bj","venue":null,"work_id":null,"year":1996},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.591320Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:8abf5cfa5154ac2a35ff40c00bf5cf88723900961217d7d660e537f467c222c6","observation_id":"0a16e087-f4b2-485a-891c-93acbd42c061","resolution":{"observed_at":"2026-08-03T17:21:27.591320Z","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":"2026-08-03T17:21:27.635657Z","title":"Advances in Neural Information Processing Systems (NeurIPS) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.635657Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:e4395b490c7016872bf04271a745385a692fe946796b285d9a3ee15c3f0921c5","observation_id":"79edb979-8788-4f8a-b871-d70d84886bd4","resolution":{"observed_at":"2026-08-03T17:21:27.635657Z","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":"2026-08-03T17:21:27.672768Z","title":"Proceedings of the International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.672768Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d585f03e33e15a1641dc929e3fdbd08624a67dd7f4187879b3bd6cb555ce542f","observation_id":"69fbdc29-751e-4a98-bf47-1c094c43a6fa","resolution":{"observed_at":"2026-08-03T17:21:27.672768Z","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":"2026-08-03T17:21:27.711112Z","title":"Proceedings of the VLDB Endowment (PVLDB) , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.711112Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:de1339adf4876c94c01caffc52b8da3d24a92906069a8303f4e1477392938a4e","observation_id":"7f79d7e0-3ae1-46bb-ab2a-c845867896fc","resolution":{"observed_at":"2026-08-03T17:21:27.711112Z","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":"2026-08-03T17:21:27.738118Z","title":"Proceedings of the 39th IEEE International Parallel and Distributed Processing Symposium (IPDPS) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.738118Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:36368fc6ff518559e044cc0b200bf7339c54dd29dacefe9750d33287a4e08fd3","observation_id":"5123c6d7-6886-4548-b630-67c197dedcbd","resolution":{"observed_at":"2026-08-03T17:21:27.738118Z","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":"2026-08-03T17:21:27.846695Z","title":"Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023) , year =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.846695Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:daf0ec29844093ca6e48a47563c3147bb7abf2b22ac65efdb99df44755ad59c7","observation_id":"5c4ba527-1fba-4726-9447-22edc0230f51","resolution":{"observed_at":"2026-08-03T17:21:27.846695Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2603.02001","last_updated":"2026-07-23T17:39:22Z","snapshot_observed_at":"2026-08-10T08:10:46.280421Z","submitted_at":"2026-03-02T15:51:45Z","title":"Bespoke OLAP: Synthesizing Workload-Specific One-size-fits-one Database Engines","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2603.02001","snapshot_observed_at":"2026-08-03T17:21:27.910620Z","title":"2026 , eprint =","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.910620Z"},"links":{"cited_paper":"/paper/2603.02001","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:62428bdb74ef52c904ef01548676097d2b3fc86aee45cc2f4ef5b6b725117d8e","observation_id":"f4ca8a9f-2225-4cc9-8ae0-84d7a8b296f7","resolution":{"observed_at":"2026-08-03T17:21:27.910620Z","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":"2026-08-03T17:21:27.993884Z","title":"2026 , eprint =","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:27.993884Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:e247b98d912a3e83d7d0f3f450e7d6175191e908448094faccf3dcaa9411444b","observation_id":"804fa36f-dfd0-4691-a1f0-678185ec46a8","resolution":{"observed_at":"2026-08-03T17:21:27.993884Z","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":"2026-08-03T17:21:28.062171Z","title":"Proceedings of the VLDB Endowment (PVLDB) , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.062171Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:c7308d94135d0371cada627190bc83b694a469a85fef79f428a6f863ed22e853","observation_id":"ffd15ec0-2683-4cbf-8691-54066c104429","resolution":{"observed_at":"2026-08-03T17:21:28.062171Z","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":"2026-08-03T17:21:28.158439Z","title":"Proceedings of the 38th Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.158439Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:8eef1266eccd69815a210da202ae7e4c1ef73555c97d6b85de1fab8cd737c377","observation_id":"ee125ad4-4404-471b-9b18-96b2e1c267ce","resolution":{"observed_at":"2026-08-03T17:21:28.158439Z","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":"2026-08-03T17:21:28.262156Z","title":"Proceedings of the 12th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.262156Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:b54d6ee5e2ea5df983dbb351eca9ece8673cae69a30fdc908c16a7f89fb7bf14","observation_id":"98296e9e-e997-4502-8b9b-2685876d5495","resolution":{"observed_at":"2026-08-03T17:21:28.262156Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-08T11:58:24.516369Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-03T17:21:28.324771Z","title":"arXiv preprint arXiv:2107.03374 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.324771Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:095791ff0de4ca2bc4f62b7714fe53ef1ac0b10b4cbbdeb8181ecf5d1e2cbd35","observation_id":"62e2d529-fe9c-4266-bac6-2d0b67630639","resolution":{"observed_at":"2026-08-03T17:21:28.324771Z","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":"2026-08-03T17:21:28.441226Z","title":"Proceedings of the International Conference on Machine Learning (ICML) , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.441226Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:415973a8931c42bec7006142459994213cc3b715ca026fbdb5ec848cdf60aaee","observation_id":"c0b6bc50-b30e-4021-b08b-4192337db660","resolution":{"observed_at":"2026-08-03T17:21:28.441226Z","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":"2026-08-03T17:21:28.527051Z","title":"Proceedings of the VLDB Endowment (PVLDB) , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.527051Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:74cc7b1c0cb3e9235e5b9cc6b3382ffed61bf06b1078a71f00e4b15feb16c7be","observation_id":"13566d5d-9b76-426f-9f2d-075c768f9ccc","resolution":{"observed_at":"2026-08-03T17:21:28.527051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.04306","last_updated":"2025-02-06T18:47:49Z","snapshot_observed_at":"2026-08-14T04:03:39.598870Z","submitted_at":"2025-02-06T18:47:49Z","title":"ScoreFlow: Mastering LLM Agent Workflows via Score-based Preference Optimization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.04306","snapshot_observed_at":"2026-08-03T17:21:28.646860Z","title":"arXiv preprint arXiv:2502.04306 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.646860Z"},"links":{"cited_paper":"/paper/2502.04306","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:99be27c918553fc8c9b70dfd789db9244d429d079eddce97579e71644347df57","observation_id":"f3c0730e-c85b-4733-8c99-a39eff0612f1","resolution":{"observed_at":"2026-08-03T17:21:28.646860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.08435","last_updated":"2025-03-02T05:13:28Z","snapshot_observed_at":"2026-08-06T11:45:45.286982Z","submitted_at":"2024-08-15T21:59:23Z","title":"Automated Design of Agentic Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.08435","snapshot_observed_at":"2026-08-03T17:21:28.708402Z","title":"arXiv preprint arXiv:2408.08435 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.708402Z"},"links":{"cited_paper":"/paper/2408.08435","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:61ce9e7ae36d53dd1b2968e39e0339b2eed03f9e91db121856be46f82ff4dd3b","observation_id":"a351ddd9-bc28-45f7-9f56-c019c3f9d719","resolution":{"observed_at":"2026-08-03T17:21:28.708402Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.12821","last_updated":"2024-07-01T21:05:02Z","snapshot_observed_at":"2026-08-13T10:41:32.572180Z","submitted_at":"2024-07-01T21:05:02Z","title":"AutoFlow: Automated Workflow Generation for Large Language Model Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.12821","snapshot_observed_at":"2026-08-03T17:21:28.776240Z","title":"arXiv preprint arXiv:2407.12821 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.776240Z"},"links":{"cited_paper":"/paper/2407.12821","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6c01860618cfdf63dc374d4e8d4146ff12cb10ee2ba5a802413b907032dc4a69","observation_id":"bcfbd22a-cc70-4821-94e1-39bc0d9d6833","resolution":{"observed_at":"2026-08-03T17:21:28.776240Z","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":"2026-08-03T17:21:28.862670Z","title":"arXiv preprint arXiv:2502.05957 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.862670Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:0cfc9220c2bb6c60b6cf5ac7f1943c3d9e188ff34130b3c59ac00fdbcbd5e7d7","observation_id":"e3c5fd77-b52c-45ad-b50e-85f8b7b284bc","resolution":{"observed_at":"2026-08-03T17:21:28.862670Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.10848","last_updated":"2023-10-23T05:05:15Z","snapshot_observed_at":"2026-08-12T18:42:32.705129Z","submitted_at":"2023-08-21T16:47:11Z","title":"AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.10848","snapshot_observed_at":"2026-08-03T17:21:28.930797Z","title":"arXiv preprint arXiv:2308.10848 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:28.930797Z"},"links":{"cited_paper":"/paper/2308.10848","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:df94433d850165416ab7f6496a23cc8a324a7d9628bb42d2db564dd8ea5421bf","observation_id":"5da06ae4-818f-4329-ae08-382ff6f9acd4","resolution":{"observed_at":"2026-08-03T17:21:28.930797Z","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":"2026-08-03T17:21:29.024613Z","title":"arXiv preprint arXiv:2502.xxxxx , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.024613Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:3dc398ef7ced6e12ac497eaa136f871c2703d9b0b7205e2d5dbea66c8f32033d","observation_id":"d8ccfe24-a3c9-432a-8425-062017745037","resolution":{"observed_at":"2026-08-03T17:21:29.024613Z","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":"2026-08-03T17:21:29.116099Z","title":"CIDR Conference , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.116099Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:90fc6f516a62c43852560abe29ce6cc3bc42b8fdf24bd0f398257c1770666949","observation_id":"709a1da9-99b8-48c2-960d-674c8211ae5e","resolution":{"observed_at":"2026-08-03T17:21:29.116099Z","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":"2026-08-03T17:21:29.162343Z","title":"PVLDB , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.162343Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:566f64237bbb5a05b0c8341b923e1d838ff251d95938c591916ccbc88f249bd6","observation_id":"e2b8fdcf-1ff6-446c-97b4-76d68e8f54eb","resolution":{"observed_at":"2026-08-03T17:21:29.162343Z","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":"2026-08-03T17:21:29.208398Z","title":"PVLDB , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.208398Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:7cfe4d5ab4afbf9609d6b2032be0433e21b986aea6781174460b176a384748dd","observation_id":"f9cc7eb7-e99c-43db-8f1a-f376d09c579f","resolution":{"observed_at":"2026-08-03T17:21:29.208398Z","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":"2026-08-03T17:21:29.250575Z","title":"2025 , url =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.250575Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:bd83445f5b06f7d53a8afdb501ebc837cfc588e23c72d33ec94ca559744adbcc","observation_id":"243f3a19-62a3-438b-895a-5e6c0a032808","resolution":{"observed_at":"2026-08-03T17:21:29.250575Z","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":"2026-08-03T17:21:29.297644Z","title":"2025 , month =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.297644Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:9d44a78f06de75c352351a0a0f78e17f05b26c41a38624ece32216aea901d4d6","observation_id":"f3fc3117-60b7-4042-96db-b209e23b27f4","resolution":{"observed_at":"2026-08-03T17:21:29.297644Z","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":"2026-08-03T17:21:29.342372Z","title":"Proceedings of the 33rd International Conference on Very Large Data Bases (VLDB) , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.342372Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:8818709b4d42ffd1a0e5f2c528b218325f2eb9386570d4385205bcd6815c246f","observation_id":"0787aea0-d72b-4f36-a8ba-8c6366e47af4","resolution":{"observed_at":"2026-08-03T17:21:29.342372Z","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":"2026-08-03T17:21:29.409729Z","title":"Foundations and Trends in Machine Learning , volume =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.409729Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d83338f7a0d17c5211ad2deebdd025af1f5cc81c1af6ff2b50bf7d85f9094eb2","observation_id":"09f3aae2-0998-4fe6-9897-aae08098cc35","resolution":{"observed_at":"2026-08-03T17:21:29.409729Z","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":"2026-08-03T17:21:29.455397Z","title":"Dalvi and Dan Suciu , title =","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.455397Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:a59007ef3acd32a1c8b0c2ba7e929a583e6ad5dfced42712949f2e6e893204f2","observation_id":"bba12bcf-d1b5-47e1-8fa1-099315f9d975","resolution":{"observed_at":"2026-08-03T17:21:29.455397Z","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":"2026-08-03T17:21:29.498917Z","title":"Information Systems Frontiers , volume =","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.498917Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:c0afcd839b23c93af223a41f27f5c28645da0ebcc795f8aff50f2cd703cb23ea","observation_id":"3bc91c95-609a-4bc7-a664-c191f8a70054","resolution":{"observed_at":"2026-08-03T17:21:29.498917Z","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":"2026-08-03T17:21:29.553016Z","title":"Frontiers Comput","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.553016Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:25e4da4c2b74aae7a118d72134e0893188795cd8c195fad0fd70e758037e833c","observation_id":"193e9de8-574e-43dc-a8e6-189b729e703b","resolution":{"observed_at":"2026-08-03T17:21:29.553016Z","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":"2026-08-03T17:21:29.581799Z","title":"Product Quantization for Nearest Neighbor Search , journal =","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.581799Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:33ee271a2c89489c7112a690a0c533780489b72fa4c86efb9d7819f5d1b313bf","observation_id":"b2f1bcbb-22c5-4ba9-bb27-41b3bfcd6474","resolution":{"observed_at":"2026-08-03T17:21:29.581799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.01108","last_updated":"2020-03-01T02:57:50Z","snapshot_observed_at":"2026-08-07T19:07:36.327251Z","submitted_at":"2019-10-02T17:56:28Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-08-03T17:21:29.662690Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.662690Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:e0f166944fe7e15d3653b8edbfeb174565e24da710e7267c0e4d123fcdc91586","observation_id":"5d49e352-1758-44db-86a8-1dd52550e7b7","resolution":{"observed_at":"2026-08-03T17:21:29.662690Z","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":"2026-08-03T17:21:29.730881Z","title":"6th International Conference on Learning Representations,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.730881Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:91ba14e4cb57467490c1abf98e7e61bd031f784803307c0b6cacc208e93bc1b4","observation_id":"7103fef5-0429-4034-b07d-997bfcf1f38a","resolution":{"observed_at":"2026-08-03T17:21:29.730881Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17152","last_updated":"2026-05-16T05:33:49Z","snapshot_observed_at":"2026-08-12T20:54:15.360404Z","submitted_at":"2025-05-22T11:11:02Z","title":"LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17152","snapshot_observed_at":"2026-08-03T17:21:29.824731Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.824731Z"},"links":{"cited_paper":"/paper/2505.17152","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:91dec7108ebec6b025adfe6ec6e2b7b8ae80df44411c8bb67cfae9615ca30d36","observation_id":"4528f756-8cd8-440c-8b66-91638430266c","resolution":{"observed_at":"2026-08-03T17:21:29.824731Z","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":"2026-08-03T17:21:29.952018Z","title":"2023 , doi =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:29.952018Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d305f8a7470ddf701def4e1ca68262b9756b6cdba5728c99dc403255e8a07276","observation_id":"54eeac41-d775-4797-aa15-d3540bea55bf","resolution":{"observed_at":"2026-08-03T17:21:29.952018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.02579","last_updated":"2025-07-09T13:45:07Z","snapshot_observed_at":"2026-08-07T15:56:22.324841Z","submitted_at":"2025-05-05T11:30:46Z","title":"EMORL: Ensemble Multi-Objective Reinforcement Learning for Efficient and Flexible LLM Fine-Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.02579","snapshot_observed_at":"2026-08-03T17:21:30.082502Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.082502Z"},"links":{"cited_paper":"/paper/2505.02579","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:8beb0dbb789abfc96b6f48c6cf4a991af8895a0bcb111ba7575dd3c4fbeab60c","observation_id":"59b839d2-902c-43d8-86a3-39dc67c35f66","resolution":{"observed_at":"2026-08-03T17:21:30.082502Z","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":"2026-08-03T17:21:30.167762Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.167762Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ce149d89be1e02119fcb8fa661d4766ee161df41979ed2a12e3dba4785a51c9f","observation_id":"aee113da-89af-485e-9096-685fbd2ad3c7","resolution":{"observed_at":"2026-08-03T17:21:30.167762Z","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":"2026-08-03T17:21:30.267582Z","title":"9th International Conference on Learning Representations,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.267582Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:81b83570d2a5ed655ea0ba3b6c841ac7036ff92523d33b7831068acb879791f9","observation_id":"69a83838-9593-4786-9793-83ef72036af0","resolution":{"observed_at":"2026-08-03T17:21:30.267582Z","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":"2026-08-03T17:21:30.414942Z","title":"Knowles and Weijie Zheng , editor =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.414942Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d177f2de8f3fa068fb45aa31ad6247c19afee1c3e554064a33fc9e39229409ba","observation_id":"58093fe2-7e5b-4ef2-b9c2-9fb6575bbede","resolution":{"observed_at":"2026-08-03T17:21:30.414942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.01989","last_updated":"2025-08-04T02:13:53Z","snapshot_observed_at":"2026-08-13T01:43:11.460965Z","submitted_at":"2025-08-04T02:13:53Z","title":"Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized LLM Serving","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.01989","snapshot_observed_at":"2026-08-03T17:21:30.483272Z","title":"Prefill-Decode Aggregation or Disaggregation? Unifying Both for Goodput-Optimized","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.483272Z"},"links":{"cited_paper":"/paper/2508.01989","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:c795b2b40b97d390a6f1cb4e513609735c339b62ddc667144089c3884c9d8045","observation_id":"eed07428-a724-46a7-8617-8c0a71d9fd2d","resolution":{"observed_at":"2026-08-03T17:21:30.483272Z","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":"2026-08-03T17:21:30.550869Z","title":"Unlocking Efficiency in Large Language Model Inference:","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.550869Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:65f1f76d12f519cd2a03d16e0b119b9bce08a14f67e654071a77066b831a86d2","observation_id":"4885bafd-1f37-47f2-8ec2-2b30e4d4e6d2","resolution":{"observed_at":"2026-08-03T17:21:30.550869Z","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":"2026-08-03T17:21:30.642985Z","title":"Deferred prefill for throughput maximization in","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.642985Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:070c9708b2620f84ba7b0e9f3a4be146632b4f5d9ee14fbc5b1872fe071efde0","observation_id":"adab6351-1086-4fb7-b323-c56dabed5e5e","resolution":{"observed_at":"2026-08-03T17:21:30.642985Z","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":"2026-08-03T17:21:30.805924Z","title":"DistServe: Disaggregating Prefill and Decoding for Goodput-optimized Large Language Model Serving , booktitle =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.805924Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:d3c516c9264b241b0edb16966d2f8ffcee3152811c74abe575f8b4510a0f4c7e","observation_id":"abb20634-666c-40b9-a0bd-8ac4ce44ff94","resolution":{"observed_at":"2026-08-03T17:21:30.805924Z","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":"2026-08-03T17:21:30.955321Z","title":"Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:30.955321Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ad54ef2c0182f7df3b034e982be133c37290343a39b4fa9c0a20ac40eb8e1f39","observation_id":"b53f2a7b-8902-42c9-b215-13916d920252","resolution":{"observed_at":"2026-08-03T17:21:30.955321Z","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":"2026-08-03T17:21:31.084527Z","title":"Ansor: Generating High-Performance Tensor Programs for Deep Learning , booktitle =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.084527Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:f5f9ee315fce3d946fda98a053a16cde4bc1e8f0c8b35b8663a490468403c721","observation_id":"9eeccc7f-9915-45ea-97e7-964086884875","resolution":{"observed_at":"2026-08-03T17:21:31.084527Z","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":"2026-08-03T17:21:31.183996Z","title":"2024 , url =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.183996Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:75df1aa200c696e0bce54d816fd555e9e0ee7df8368b801eec3780a1ac1af202","observation_id":"b5063376-663a-4af1-aca0-e05732a90343","resolution":{"observed_at":"2026-08-03T17:21:31.183996Z","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":"2026-08-03T17:21:31.283448Z","title":"Ilyas and Theodoros Rekatsinas and Shivaram Venkataraman , editor =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.283448Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:a2e15e538a7f439df55f29f809ffef6bf671c026b8b67d9f7532b6bf1b9f2e06","observation_id":"50c80e75-2c52-4a62-a744-56987c147e20","resolution":{"observed_at":"2026-08-03T17:21:31.283448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.17152","last_updated":"2026-05-16T05:33:49Z","snapshot_observed_at":"2026-08-12T20:54:15.360404Z","submitted_at":"2025-05-22T11:11:02Z","title":"LSM-VEC: A Large-Scale Disk-Based System for Dynamic Vector Search","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.17152","snapshot_observed_at":"2026-08-03T17:21:31.397277Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.397277Z"},"links":{"cited_paper":"/paper/2505.17152","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:cd7db567727baae814b3f3aac56b309129fc337a2abfe13941027ccf5cd4d3a5","observation_id":"df876bc3-4474-4949-b163-5112ca607bd7","resolution":{"observed_at":"2026-08-03T17:21:31.397277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.05276","last_updated":"2024-12-09T01:44:10Z","snapshot_observed_at":"2026-08-12T22:05:08.125471Z","submitted_at":"2024-11-08T02:21:19Z","title":"GPT Semantic Cache: Reducing LLM Costs and Latency via Semantic Embedding Caching","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.05276","snapshot_observed_at":"2026-08-03T17:21:31.510856Z","title":"CoRR , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.510856Z"},"links":{"cited_paper":"/paper/2411.05276","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:9120bd1f7fe8b1269c3b0ae0d22f26c4fd5c44e7b66dee9d3d49bce5b47581b4","observation_id":"a2b46e7d-c2d3-4789-9f7a-ee35225677a1","resolution":{"observed_at":"2026-08-03T17:21:31.510856Z","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":"2026-08-03T17:21:31.653250Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.653250Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ca68f3a04aafefcfe9639e530e8a934e9c6ec58886b8047940c6dfb203d5b927","observation_id":"de58e4f2-575e-46fc-8eec-5dfa63d53895","resolution":{"observed_at":"2026-08-03T17:21:31.653250Z","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":"2026-08-03T17:21:31.760429Z","title":"The Twelfth International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.760429Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:653cbe034de77034589ea1bb175444ca19f9e8e60c2a11afeefcc7ee7f125461","observation_id":"a561b949-0e91-407e-976d-458bc09b595a","resolution":{"observed_at":"2026-08-03T17:21:31.760429Z","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":"2026-08-03T17:21:31.865753Z","title":"The Twelfth International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.865753Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ddc111d6d035dee0f8231920e8bc45adf4846573ef311b8731d3c79e30027e4c","observation_id":"a0a0bbe1-85dc-46a6-b4ce-c9f10faa27fb","resolution":{"observed_at":"2026-08-03T17:21:31.865753Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15594","last_updated":"2025-10-19T10:32:43Z","snapshot_observed_at":"2026-08-13T06:43:22.011336Z","submitted_at":"2024-11-23T16:03:35Z","title":"A Survey on LLM-as-a-Judge","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15594","snapshot_observed_at":"2026-08-03T17:21:31.997331Z","title":"10.48550/arXiv.2411.15594 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:31.997331Z"},"links":{"cited_paper":"/paper/2411.15594","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:0a4f00bfb32efdd70cd5aa50e21cef1501d97df13b05b80ed71013800fd9f863","observation_id":"fefb62c8-f6f5-4518-8bb8-a1795ae9b6e5","resolution":{"observed_at":"2026-08-03T17:21:31.997331Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.05958","last_updated":"2025-06-27T10:11:00Z","snapshot_observed_at":"2026-08-12T19:26:38.861031Z","submitted_at":"2024-12-08T14:34:30Z","title":"Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.05958","snapshot_observed_at":"2026-08-03T17:21:32.115847Z","title":"Towards Modeling Human-Agentic Collaborative Workflows: A BPMN Extension , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.115847Z"},"links":{"cited_paper":"/paper/2412.05958","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:97701d73cb8296a64a8e6d9a207998d28b53215fb03774467a1b771e45f2e92b","observation_id":"fe5cbed1-561f-45aa-9d77-6d3e921b9174","resolution":{"observed_at":"2026-08-03T17:21:32.115847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.22473","last_updated":"2025-03-28T14:33:29Z","snapshot_observed_at":"2026-08-07T16:30:09.608936Z","submitted_at":"2025-03-28T14:33:29Z","title":"WorkTeam: Constructing Workflows from Natural Language with Multi-Agents","version":1},"cited_work":{"arxiv_id":"2503.22473","doi":"10.48550/arxiv.2503.22473","metadata_source":"pith","pith_arxiv_id":"2503.22473","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"WorkTeam: Constructing Workflows from Natural Language with Multi-Agents","venue":"cs.CL","work_id":"44675a85-8712-4cba-87e4-2a389a047025","year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.246588Z"},"links":{"cited_paper":"/paper/2503.22473","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:79983e11b11eeba4058b7bacfaba8127afe29054ce244de41c968c2291951443","observation_id":"b2a8db5c-49ba-4196-a567-247d895727ca","resolution":{"observed_at":"2026-08-03T17:23:24.764524Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2508.02470","last_updated":"2025-08-04T14:36:31Z","snapshot_observed_at":"2026-08-07T16:07:22.433481Z","submitted_at":"2025-08-04T14:36:31Z","title":"AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration","version":1},"cited_work":{"arxiv_id":"2508.02470","doi":"10.48550/arxiv.2508.02470","metadata_source":"pith","pith_arxiv_id":"2508.02470","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration","venue":"cs.HC","work_id":"48e8f8e9-52b1-4c73-a148-b6e1f8555464","year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.314806Z"},"links":{"cited_paper":"/paper/2508.02470","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:df362f1f42e781b028e998a4c04661cbcc2b77a05eb74983f219e2b84f4dc74f","observation_id":"8dbceb4d-b63f-469f-887f-338fb7f67e9a","resolution":{"observed_at":"2026-08-03T17:23:24.642858Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+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":"2026-08-03T17:21:32.398499Z","title":"ICLR , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.398499Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6098791d7d5d504fc2f00e4eaf72bfb15af0885972a41d2b3ca687838016c173","observation_id":"0c325565-94c0-4daf-819a-aaefeb6f5b6a","resolution":{"observed_at":"2026-08-03T17:21:32.398499Z","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":"2026-08-03T17:21:32.543546Z","title":"and Parameswaran, Aditya G","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.543546Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:158b16be772a86b299e1d4697c8f0739c384c99c87339d270f70456a57b9f318","observation_id":"d1788861-09b1-437d-aa86-61bfb2305548","resolution":{"observed_at":"2026-08-03T17:21:32.543546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.02286","last_updated":"2024-03-04T18:17:18Z","snapshot_observed_at":"2026-08-13T04:03:46.925474Z","submitted_at":"2024-03-04T18:17:18Z","title":"Stage: Query Execution Time Prediction in Amazon Redshift","version":1},"cited_work":{"arxiv_id":"2403.02286","doi":"10.48550/arxiv.2403.02286","metadata_source":"pith","pith_arxiv_id":"2403.02286","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Stage: Query Execution Time Prediction in Amazon Redshift","venue":"cs.DB","work_id":"7b41b058-9560-4c61-99d7-7c00a6b76c5b","year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.630296Z"},"links":{"cited_paper":"/paper/2403.02286","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:9a6f33220f86d33840b7db604acf3d8f9c326ca394b44cb7e2303f96ccc4c932","observation_id":"ac37c3a2-455b-4ed7-ada3-e212ff9f5468","resolution":{"observed_at":"2026-08-03T17:23:24.502637Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.02153","last_updated":"2025-09-15T22:15:00Z","snapshot_observed_at":"2026-08-12T13:48:47.535846Z","submitted_at":"2025-06-02T18:35:16Z","title":"Small Language Models are the Future of Agentic AI","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.02153","snapshot_observed_at":"2026-08-03T17:21:32.737599Z","title":"10.48550/arXiv.2506.02153 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.737599Z"},"links":{"cited_paper":"/paper/2506.02153","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:0029582bedbb3d467f45883128553956d4c2d005d174d976f29865cbc48c2bf2","observation_id":"93a4add5-cb74-4eed-bc58-5fe0ba7ce455","resolution":{"observed_at":"2026-08-03T17:21:32.737599Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.19807","last_updated":"2025-08-27T11:50:42Z","snapshot_observed_at":"2026-08-05T15:31:14.634045Z","submitted_at":"2025-08-27T11:50:42Z","title":"Bootstrapping Learned Cost Models with Synthetic SQL Queries","version":1},"cited_work":{"arxiv_id":"2508.19807","doi":"10.48550/arxiv.2508.19807","metadata_source":"pith","pith_arxiv_id":"2508.19807","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Bootstrapping Learned Cost Models with Synthetic SQL Queries","venue":"cs.DB","work_id":"d521eff8-0a18-49e8-a43c-1627938e2dcf","year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.836546Z"},"links":{"cited_paper":"/paper/2508.19807","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:efe100a2015b5ac271078ccff689d1d4507d42adda7732b22f3c3a6f9963b016","observation_id":"16880630-909b-4e69-a317-07912ef84265","resolution":{"observed_at":"2026-08-03T17:23:24.340829Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/2024.emnlp-industry.74","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Adapting LLMs for Structured Natural Language API Integration , url=","venue":null,"work_id":"3cd9bae3-1fb1-4b76-9852-03ebb3521bc5","year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.886923Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:48dc856772fbb2157e5592c79b4418e249ca3053325d22e3f0f3a9cb7af0d05e","observation_id":"86cb7f6f-2c39-498f-b298-514ec683d3e0","resolution":{"observed_at":"2026-08-03T17:23:24.184957Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.17111","last_updated":"2025-06-20T16:11:25Z","snapshot_observed_at":"2026-08-07T00:10:50.823267Z","submitted_at":"2025-06-20T16:11:25Z","title":"Are Bias Evaluation Methods Biased ?","version":1},"cited_work":{"arxiv_id":"2506.17111","doi":"10.48550/arxiv.2506.17111","metadata_source":"pith","pith_arxiv_id":"2506.17111","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Are Bias Evaluation Methods Biased ?","venue":"cs.AI","work_id":"673f6c48-c38c-4490-93b9-767f1e56cc96","year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:32.954400Z"},"links":{"cited_paper":"/paper/2506.17111","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:335ec69550b993a04039b1c9f3b323eb4c590221eca63c88cf4ccd7450617c83","observation_id":"7f0e60d6-99df-47a2-b403-69f4a8987242","resolution":{"observed_at":"2026-08-03T17:23:24.063374Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.02802","last_updated":"2025-06-03T12:32:56Z","snapshot_observed_at":"2026-08-14T09:33:50.819632Z","submitted_at":"2025-06-03T12:32:56Z","title":"A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads","version":1},"cited_work":{"arxiv_id":"2506.02802","doi":"10.48550/arxiv.2506.02802","metadata_source":"pith","pith_arxiv_id":"2506.02802","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"A Learned Cost Model-based Cross-engine Optimizer for SQL Workloads","venue":"cs.DB","work_id":"b41bf6ef-0775-4612-ad62-7d52ce96de2e","year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.016716Z"},"links":{"cited_paper":"/paper/2506.02802","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ea422b65b07aad50fc205b8dc38c457477898728fff095c2e8abae31023ac551","observation_id":"26592325-7e17-4a2b-a224-e7b1b6e6be6b","resolution":{"observed_at":"2026-08-03T17:23:23.933408Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.05780","last_updated":"2025-07-09T12:28:00Z","snapshot_observed_at":"2026-08-07T17:46:37.204285Z","submitted_at":"2025-02-26T12:23:14Z","title":"AI Risk Atlas: Taxonomy and Tooling for Navigating AI Risks and Resources","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.05780","snapshot_observed_at":"2026-08-03T17:21:33.068987Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.068987Z"},"links":{"cited_paper":"/paper/2503.05780","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ad54a97aee69b5e5f0a91ef018e39aad6084c0b283cd673fc078f4fb043ab52e","observation_id":"a2fc57e4-5fa0-4108-82c3-ca448ae25a35","resolution":{"observed_at":"2026-08-03T17:21:33.068987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.13050","last_updated":"2024-03-17T00:36:37Z","snapshot_observed_at":"2026-08-13T00:52:42.031983Z","submitted_at":"2024-03-17T00:36:37Z","title":"FlowMind: Automatic Workflow Generation with LLMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.13050","snapshot_observed_at":"2026-08-03T17:21:33.111803Z","title":"FlowMind: Automatic Workflow Generation with LLMs , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.111803Z"},"links":{"cited_paper":"/paper/2404.13050","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:498f72c695aa4c0cc60fa72d1d51f5c50b7ac0288602625005a98d2807c02ab4","observation_id":"b2cc8e56-416a-4acb-9875-9a2e95eef49d","resolution":{"observed_at":"2026-08-03T17:21:33.111803Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.08189","last_updated":"2024-04-12T01:42:09Z","snapshot_observed_at":"2026-08-13T21:35:49.187420Z","submitted_at":"2024-04-12T01:42:09Z","title":"Reducing hallucination in structured outputs via Retrieval-Augmented Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.08189","snapshot_observed_at":"2026-08-03T17:21:33.172183Z","title":"Reducing hallucination in structured outputs via Retrieval-Augmented Generation , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.172183Z"},"links":{"cited_paper":"/paper/2404.08189","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:a94797a104a92ba2186f1ad3960e13e58b977f82149fc43d2b8cb470018cce26","observation_id":"bb8c9bf5-c28d-4a47-bda8-e75e8360503a","resolution":{"observed_at":"2026-08-03T17:21:33.172183Z","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":"2026-08-03T17:21:33.225457Z","title":"The Eleventh International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.225457Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:370dc04ed86a059a24a9abdd25671ad7f326d398bd5a8f79354ba1bc78548330","observation_id":"fa1f95e3-6805-4c57-a838-09b102fd5a79","resolution":{"observed_at":"2026-08-03T17:21:33.225457Z","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":"2026-08-03T17:21:33.322379Z","title":"Self-planning Code Generation with Large Language Models , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.322379Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6010ef75a1ba09be37dd5fd9224971f507c5df6b841aeadd2d40fde4e4bdb813","observation_id":"3fdaef4d-3615-41d9-8fa6-943dbd775371","resolution":{"observed_at":"2026-08-03T17:21:33.322379Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.07864","last_updated":"2023-09-19T08:29:18Z","snapshot_observed_at":"2026-08-09T18:54:02.679174Z","submitted_at":"2023-09-14T17:12:03Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.07864","snapshot_observed_at":"2026-08-03T17:21:33.493790Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.493790Z"},"links":{"cited_paper":"/paper/2309.07864","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:a734535137dd95e90c68e16091d5864beb455d371fc591f518138be8eeef211a","observation_id":"bd76192b-7548-4948-8d30-602de354bbbf","resolution":{"observed_at":"2026-08-03T17:21:33.493790Z","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":"2026-08-03T17:21:33.583119Z","title":"TPTU: Large Language Model-based AI Agents for Task Planning and Tool Usage , url=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.583119Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:69c982a1cb242da97556e8e44f56a0c96d5c820357f285da76592245c623de35","observation_id":"cc4f337a-810f-402d-a61b-ad5d03247048","resolution":{"observed_at":"2026-08-03T17:21:33.583119Z","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":"2026-08-03T17:21:33.743154Z","title":"ICLR , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.743154Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:1bcee6e44c563d4304203bacde1bc081545488fa5a309083c899ae0d42983a61","observation_id":"31cd550f-5708-4d32-872b-87f6a563be8d","resolution":{"observed_at":"2026-08-03T17:21:33.743154Z","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":"2026-08-03T17:21:33.897050Z","title":"10.48550/arXiv.2502.05957 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:33.897050Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:81be81c9ce56c39b9bdbc5e770187e0ed9c8a9e5f61c2f7a5fdd0de7309d6551","observation_id":"1bd7cfdc-8a79-4d65-ad31-23f4a3af927d","resolution":{"observed_at":"2026-08-03T17:21:33.897050Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.17760","last_updated":"2023-11-02T17:34:57Z","snapshot_observed_at":"2026-08-13T20:29:29.004177Z","submitted_at":"2023-03-31T01:09:00Z","title":"CAMEL: Communicative Agents for \"Mind\" Exploration of Large Language Model Society","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.17760","snapshot_observed_at":"2026-08-03T17:21:34.059504Z","title":"Proceedings of the 37th International Conference on Neural Information Processing Systems (NeurIPS) , author=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":91,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.059504Z"},"links":{"cited_paper":"/paper/2303.17760","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:cd9dffa43369767b8cc5d334b59a77d958ef7b04f14002aae422e2eac91e6150","observation_id":"7fcc8542-e287-4fce-9bb7-a7122c7e2575","resolution":{"observed_at":"2026-08-03T17:21:34.059504Z","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":"2026-08-03T17:21:34.205732Z","title":"ICLR , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":92,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.205732Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:646605138170ca8c13d5a3025bf7c6dd56ae15adf0ca6039fdca26904e1f774f","observation_id":"9d1cc064-8616-463b-967f-5482acb6b251","resolution":{"observed_at":"2026-08-03T17:21:34.205732Z","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":"2026-08-03T17:21:34.318781Z","title":"Differentiation","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":93,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.318781Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:01b8fbbf052575a77d60052c103def4773f8c1a7dd6a33c29dfbb895b9d43b5a","observation_id":"c5fe9342-8a32-4498-afca-c9c09db16dd6","resolution":{"observed_at":"2026-08-03T17:21:34.318781Z","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":"2026-08-03T17:21:34.430682Z","title":"Forty-first International Conference on Machine Learning (ICML) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":94,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.430682Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:897f343aa40a776c93797f7cfd3d496a8d1496abb6ff9dd4d4b00ec14a45c7d7","observation_id":"8f46b5ad-4a17-4ec4-a88e-3d281acce8a6","resolution":{"observed_at":"2026-08-03T17:21:34.430682Z","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":"2026-08-03T17:21:34.491787Z","title":"A Dynamic","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":95,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.491787Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:e5fce8f781b011320ad9682fe00990cbac10e8261a6a9feeab7f57dd1d4773ac","observation_id":"708e37ce-c1c6-4bc1-90f6-84ce7f13e5fc","resolution":{"observed_at":"2026-08-03T17:21:34.491787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.04808","last_updated":"2025-04-14T19:46:56Z","snapshot_observed_at":"2026-08-13T21:34:08.034098Z","submitted_at":"2025-04-07T08:03:36Z","title":"ELT-Bench: An End-to-End Benchmark for Evaluating AI Agents on ELT Pipelines","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.04808","snapshot_observed_at":"2026-08-03T17:21:34.637001Z","title":"10.48550/arXiv.2504.04808 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":96,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.637001Z"},"links":{"cited_paper":"/paper/2504.04808","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:f23cd300a01b0314ef7aef347fd31893730ed161c4ffba46d49d6b47024c60ea","observation_id":"00f033ae-040f-407e-b401-b2cceecace52","resolution":{"observed_at":"2026-08-03T17:21:34.637001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13897","last_updated":"2025-02-19T17:31:51Z","snapshot_observed_at":"2026-08-07T18:04:25.069863Z","submitted_at":"2025-02-19T17:31:51Z","title":"DataSciBench: An LLM Agent Benchmark for Data Science","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13897","snapshot_observed_at":"2026-08-03T17:21:34.733190Z","title":"10.48550/arXiv.2502.13897 , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":97,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.733190Z"},"links":{"cited_paper":"/paper/2502.13897","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:ec24fc910b590a1ef7948543a268e6aa900771aa4c4c2a78d6aaf4e51325960d","observation_id":"541ae512-bc90-49e3-89bf-f6c41e3f15eb","resolution":{"observed_at":"2026-08-03T17:21:34.733190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.03111","last_updated":"2023-11-15T04:56:25Z","snapshot_observed_at":"2026-08-13T11:49:04.089987Z","submitted_at":"2023-05-04T19:02:29Z","title":"Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.03111","snapshot_observed_at":"2026-08-03T17:21:34.879997Z","title":"Proceedings of the 37th International Conference on Neural Information Processing Systems (NeurIPS) , author=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":98,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:34.879997Z"},"links":{"cited_paper":"/paper/2305.03111","citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:e29245c971c88cde33bd1663290ec586d2cf727279cb912adf83a2d84590a0cd","observation_id":"ddef29b0-905d-448f-90fd-aa053c2ff138","resolution":{"observed_at":"2026-08-03T17:21:34.879997Z","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":"2026-08-03T17:21:35.019826Z","title":"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) , author=","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":99,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:35.019826Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:6c0094233759b7f06403a39377849e602eeaf4a47672e2cef7aafd492f53bd56","observation_id":"0b2f569a-6844-4ed0-bec3-a91077969567","resolution":{"observed_at":"2026-08-03T17:21:35.019826Z","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":"2026-08-03T17:21:35.117582Z","title":"Alfonso and Martínez Cámara, Eugenio and Camacho-Collados, Jose , editor=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]","version":2},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-08-03T17:21:35.117582Z"},"links":{"citing_paper":"/paper/2512.11001"},"observation_digest":"sha256:feb9767b5cddbfb0baf123f936d29c5ff9c5e8b26f720db8e94b6a408fbaac08","observation_id":"b102ea2b-786c-4674-9bc9-e7fe1541295d","resolution":{"observed_at":"2026-08-03T17:21:35.117582Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2512.11001","last_updated":"2026-07-07T14:01:07Z","latest_version":2,"primary_category":"cs.DB","snapshot_observed_at":"2026-08-12T13:49:43.584085Z","submitted_at":"2025-12-10T20:16:20Z","title":"Rethinking Query Optimization for Multi-Agent Systems [Vision]"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":0,"metadata_mismatch":3,"parse_uncertain":0,"unresolved":92,"verified_exact":5,"verified_fuzzy":0},"total_outbound_references":171},"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":"2026-08-14T06:32:32.682623+00:00","source":"crossref"},{"observed_at":"2026-08-14T06:32:18.44784+00:00","source":"retraction_watch"}],"thesis":"As of 14 August 2026, this Paper Citation Record lists 100 of 171 outbound references and 0 inbound Pith citation observations for arXiv:2512.11001."}