{"as_of":"2026-08-09T11:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:efa9c1b89f4f08138b5776d2d59ac336e86f542f0497023ded4fa9ec6ad0aec9","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":7,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":7,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":7,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":7,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T13:12:45.462728Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-15T19:56:33.673543Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-08-07T13:12:45.462728Z","title":"Mag-sql: Multi-agent generative approach with soft schema linking and iterative sub-sql refinement for text-to-sql","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.23838","last_updated":"2025-05-28T13:23:38Z","snapshot_observed_at":"2026-08-09T04:39:49.673472Z","submitted_at":"2025-05-28T13:23:38Z","title":"Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunities","version":1},"reference_index":139,"source":"pdf_text","source_observed_at":"2026-08-07T13:12:45.462728Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2505.23838"},"observation_digest":"sha256:3ebd56ac66fc7236b0de788088ad8f91f841e303f7e85f9ad04acd43fd8d8267","observation_id":"cafddf35-e084-499d-b5ca-4763cea20529","resolution":{"observed_at":"2026-08-07T13:12:45.462728Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-08-07T05:43:49.622152Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.07245","last_updated":"2025-06-19T04:10:10Z","snapshot_observed_at":"2026-08-09T07:12:39.097138Z","submitted_at":"2025-06-08T18:01:26Z","title":"SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probes","version":2},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-07T05:43:49.622152Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2506.07245"},"observation_digest":"sha256:835f24df287c9cbe6eb45a8dac888735c6b32ae62046b2203e062ddcd8315cbb","observation_id":"98d67c5e-3550-4ee1-a5cf-6b7af737efb7","resolution":{"observed_at":"2026-08-07T05:43:49.622152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-08-06T10:47:55.110380Z","title":", author Wu, G","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.23429","last_updated":"2025-07-31T11:09:50Z","snapshot_observed_at":"2026-08-06T10:47:36.339170Z","submitted_at":"2025-07-31T11:09:50Z","title":"Chatting with your ERP: A Recipe","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-06T10:47:55.110380Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2507.23429"},"observation_digest":"sha256:8074b0758c08d6d97516e8268d3ab94a375b17c8749b5845737eb52eb3acda5d","observation_id":"804794e9-d54a-41e2-aba3-db67f1985eb7","resolution":{"observed_at":"2026-08-06T10:47:55.110380Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-08-03T01:04:46.388222Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.16720","last_updated":"2026-05-31T14:34:05Z","snapshot_observed_at":"2026-08-07T00:33:11.064016Z","submitted_at":"2026-02-11T07:50:47Z","title":"APEX-SQL: Talking to the data via Agentic Exploration for Text-to-SQL","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-03T01:04:46.388222Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2602.16720"},"observation_digest":"sha256:c9087795d8d45c92404f9602ce80840a2612efc48215d341133b8c70cc5f6653","observation_id":"39057bcf-a540-4d92-bd83-d9855ac10dbd","resolution":{"observed_at":"2026-08-03T01:04:46.388222Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":"2408.07930","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2408.07930 , year=","venue":null,"work_id":"97d1b306-5937-407f-9af0-c30e9629d900","year":2024},"citing_paper":{"arxiv_id":"2602.21480","last_updated":"2026-04-13T13:29:15Z","snapshot_observed_at":"2026-08-08T12:33:02.215797Z","submitted_at":"2026-02-25T01:12:35Z","title":"Both Ends Count! Just How Good are LLM Agents at \"Text-to-Big SQL\"?","version":4},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-15T19:52:53.443887Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2602.21480"},"observation_digest":"sha256:41bc9f0e77e83940fd6805b01b93d58bb6bf4cae639c41993c32ab08abeaaf3d","observation_id":"78b3a9d9-92f6-4942-9d25-a4971dd93b0a","resolution":{"observed_at":"2026-05-15T19:56:33.678224Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":"2408.07930","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2408.07930 , year=","venue":null,"work_id":"97d1b306-5937-407f-9af0-c30e9629d900","year":2024},"citing_paper":{"arxiv_id":"2605.04065","last_updated":"2026-05-07T04:49:30Z","snapshot_observed_at":"2026-07-06T23:16:54.673178Z","submitted_at":"2026-04-11T07:26:04Z","title":"Free Energy-Driven Reinforcement Learning with Adaptive Advantage Shaping for Unsupervised Reasoning in LLMs","version":2},"reference_index":208,"source":"arxiv_source","source_observed_at":"2026-05-10T16:58:10.013475Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2605.04065"},"observation_digest":"sha256:2478c994b3dd9fe5069529237f2d591b8edb07b021b1fc964eca0df7c503f806","observation_id":"bba7abbc-968d-4f4f-90a1-a0799baff0da","resolution":{"observed_at":"2026-05-11T07:45:59.603474Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL","version":4},"cited_work":{"arxiv_id":"2408.07930","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2408.07930","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2408.07930 , year=","venue":null,"work_id":"97d1b306-5937-407f-9af0-c30e9629d900","year":2024},"citing_paper":{"arxiv_id":"2605.04066","last_updated":"2026-05-07T04:57:40Z","snapshot_observed_at":"2026-08-02T15:49:26.057284Z","submitted_at":"2026-04-11T07:34:59Z","title":"Adapt to Thrive! Adaptive Power-Mean Policy Optimization for Improved LLM Reasoning","version":2},"reference_index":193,"source":"arxiv_source","source_observed_at":"2026-05-10T16:51:19.555272Z"},"links":{"cited_paper":"/paper/2408.07930","citing_paper":"/paper/2605.04066"},"observation_digest":"sha256:cab8f8514ed0c2d42742525f48d9b881cf0c1c98c62b3e9c73fe8fde7ac69f1d","observation_id":"44d3cd40-89d2-497e-836e-c17e9c488b7f","resolution":{"observed_at":"2026-05-11T08:01:00.069423Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2408.07930/citation-record","integrity":"/paper/2408.07930/integrity","json":"/paper/2408.07930/citation-record.json","paper":"/paper/2408.07930"},"outbound":[],"paper":{"arxiv_id":"2408.07930","last_updated":"2024-11-07T03:37:51Z","latest_version":4,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-09T06:35:21.322645Z","submitted_at":"2024-08-15T04:57:55Z","title":"MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQL"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2408.07930."}