{"as_of":"2026-08-15T22:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:49ec3f4e0530c0c7dd6868a6f9cb7caadb968c901f35ed4a6dc1084dda0eab60","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T18:18:35.831633Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-15T00:18:22.361169Z","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":"2026-05-15T00:19:35.432035Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"cited_work":{"arxiv_id":"2412.10434","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.10434","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Nat-nl2gql: A novel multi-agent framework for translating natural language to graph query language","venue":null,"work_id":"e2f04c9b-5fff-47e6-9d4d-4529e41013c5","year":2024},"citing_paper":{"arxiv_id":"2603.23375","last_updated":"2026-03-24T16:06:10Z","snapshot_observed_at":"2026-08-09T01:47:07.554222Z","submitted_at":"2026-03-24T16:06:10Z","title":"Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directions","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-15T00:18:22.361169Z"},"links":{"cited_paper":"/paper/2412.10434","citing_paper":"/paper/2603.23375"},"observation_digest":"sha256:b1ba3da33ba6faf861028ffb2c7e5d3385d406dd8a3bae48fc1fe851e40d8e03","observation_id":"577659fd-a796-4097-b822-644df586125a","resolution":{"observed_at":"2026-05-15T00:19:35.433560Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.10434/citation-record","integrity":"/paper/2412.10434/integrity","json":"/paper/2412.10434/citation-record.json","paper":"/paper/2412.10434"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2202.08871","last_updated":"2023-01-19T01:26:16Z","snapshot_observed_at":"2026-08-14T09:13:30.434442Z","submitted_at":"2022-02-17T19:14:17Z","title":"Graph Data Augmentation for Graph Machine Learning: A Survey","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2202.08871","snapshot_observed_at":"2026-08-11T18:18:34.793340Z","title":"Graph data augmentation for graph machine learning: A survey,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:34.793340Z"},"links":{"cited_paper":"/paper/2202.08871","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:8d47792c7add5c8e1e108e982c0886291af507ab71a42b3862c94a961832c7a8","observation_id":"39b5970b-9c92-4880-b729-b5f8d1d2e79c","resolution":{"observed_at":"2026-08-11T18:18:34.793340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.660990Z","title":"Unleashing the power of graph data augmentation on covariate dis- tribution shift,","venue":null,"work_id":"7131b78f-92f1-4222-b342-d4171a31a21e","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:34.889146Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:a3dd6d8f7c44a2547a3ded48104707621e3ae2f1ca0f907a125100c5acaedc03","observation_id":"88b69338-22bc-4d38-b505-7a69ead9529b","resolution":{"observed_at":"2026-08-11T18:18:37.667394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.643170Z","title":"Graph databases: An alternative to relational databases in an interconnected big data environment,","venue":null,"work_id":"1ab7f200-5b6e-4d67-8ff4-89835354cfb4","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:34.983872Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:39df6b7656b20041f0165c52d6d7deda075eb19d7ca5a670cf6e674cf89bca53","observation_id":"2cd0b2de-9b3e-4a79-985d-e6321f0d398e","resolution":{"observed_at":"2026-08-11T18:18:37.649134Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.623232Z","title":"Scalability and performance evaluation of graph database systems: A comparative study of neo4j, janusgraph, memgraph, nebu- lagraph, and tigergraph,","venue":null,"work_id":"8d8edc36-2c36-461a-8c47-88e3ad9335ac","year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:34.990014Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:cfb9d2c7a2c5eb6bce07ef579d9723f5ea05e4baa4a0822bca4d5b57386a8eec","observation_id":"defb4f81-5f79-4db5-b9e4-7c013c3e985f","resolution":{"observed_at":"2026-08-11T18:18:37.629561Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.601257Z","title":"An empirical study on recent graph database systems,","venue":null,"work_id":"2bb78de9-bcf3-4096-982d-85be409981ee","year":2020},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:34.995126Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:ce9a3b07ff12368206c1dce241b3717eb861522d4936969da8d85d23719fd799","observation_id":"da94dc0f-144f-47a7-a02e-44ff9568a639","resolution":{"observed_at":"2026-08-11T18:18:37.608803Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-11T18:18:35.001250Z","title":"Spcql: A semantic parsing dataset for converting natural language into cypher,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.001250Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:7b8a193553ca1a8d82cc279bf568af88f26c346b1fc691b0468dabf5aa6dc85c","observation_id":"e88e3ae6-8bfa-4d9d-a8b9-1407f1e774c5","resolution":{"observed_at":"2026-08-11T18:18:35.001250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.463839Z","title":"Aligning large language models to a domain-specific graph database for nl2gql,","venue":null,"work_id":"c8c2b3a2-0802-41fc-bae5-3373d55d6e60","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.007233Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:cf59bb57c5eb8245e49fe7e9aac14027f174ee2fabc2fedd133b17e69d376c8d","observation_id":"57d84acb-62da-48d1-a02a-3f0ae5375cc7","resolution":{"observed_at":"2026-08-11T18:18:37.549637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.264391Z","title":"r3-NL2GQL: A model coordination and knowledge graph alignment approach for NL2GQL,","venue":null,"work_id":"84a05a62-fb1e-4ea4-9b75-8ae0ad92ab17","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.012986Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:cdd6f7343f547c98c84246f77e491d84a41b036786f36da689ca8495cba07c44","observation_id":"5ca16612-fb06-4b3d-ae24-9bed540ba27f","resolution":{"observed_at":"2026-08-11T18:18:37.378644Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.245880Z","title":"Cyspider: A neural semantic parsing corpus with baseline models for property graphs,","venue":null,"work_id":"b0da60ec-fe60-483d-a460-ebc551fa2982","year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.019404Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:e141744b66e06e3c594f87f2ba0f1884acc0829402782049035226a50e3c1c8a","observation_id":"698752ba-2d4f-4eb2-8558-7e8f30eda3b4","resolution":{"observed_at":"2026-08-11T18:18:37.251925Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.225712Z","title":"Robust text-to-cypher using combination of bert, graphsage, and transformer (cobgt) model,","venue":null,"work_id":"16ae68ba-8077-4702-a3ad-c35da6d53524","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.025141Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:7784a2244e857a44f89dd5df72fd7a394cea8b9d582861f3ca08e99f7979f68e","observation_id":"ec1b2134-5be2-44fc-a959-0ea83fd9f1cf","resolution":{"observed_at":"2026-08-11T18:18:37.233781Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-11T18:18:35.029810Z","title":"Inductive representation learning on large graphs,","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.029810Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:41a0e0411fdb4e3b1d0002452450c7b4f0b6495c96bb6ec96a4a5fe42ef81b49","observation_id":"4973c14d-83b6-4d7c-bed6-05092c713a07","resolution":{"observed_at":"2026-08-11T18:18:35.029810Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:37.163973Z","title":"Kei-cql: A keyword extraction and infilling framework for text to cypher query language translation","venue":null,"work_id":"dcaef10e-154c-4e29-b8e2-7d018515dc1a","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.034675Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:de1accd200d80c9bca4149d056da726032332226aecee01a4cfccf3b865f31ea","observation_id":"a62fe230-26b4-4b98-8325-24728f326bb3","resolution":{"observed_at":"2026-08-11T18:18:37.199084Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.927585Z","title":"Autotqa: Towards autonomous tabular question answering through multi-agent large language models,","venue":null,"work_id":"68f2e083-ca8f-4468-b555-4987fe811679","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.096073Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:d971c4aa14a104007d0412ebb0be8fbead7459733bc2fa86c8f21d1f5398fe92","observation_id":"e44b8b1b-bc33-4ed1-a653-d26058efae2d","resolution":{"observed_at":"2026-08-11T18:18:37.030991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.20014","last_updated":"2024-03-29T07:01:29Z","snapshot_observed_at":"2026-08-13T00:42:23.922480Z","submitted_at":"2024-03-29T07:01:29Z","title":"PURPLE: Making a Large Language Model a Better SQL Writer","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.20014","snapshot_observed_at":"2026-08-11T18:18:35.172641Z","title":"Purple: Making a large language model a better sql writer,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.172641Z"},"links":{"cited_paper":"/paper/2403.20014","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:2112c9a94cffb882b4fab997ccc95420d408de877a984209005c3b8ea5d0d8c2","observation_id":"0084973b-023b-4be7-9b91-5c9020691ae4","resolution":{"observed_at":"2026-08-11T18:18:35.172641Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.885584Z","title":"Online index recommendation for slow queries,","venue":null,"work_id":"f5dfd1c3-cfb4-44ee-974f-805e1a89c9d5","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.179474Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:65d4b1d4a2120d8e8ee71e796b20b4ee3b5dcfd8838f3961fcfc449e6419b50f","observation_id":"ca2446bb-cf61-42b2-a67f-885d22046e00","resolution":{"observed_at":"2026-08-11T18:18:36.891437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.01454","last_updated":"2023-12-06T02:53:11Z","snapshot_observed_at":"2026-08-13T05:10:54.736711Z","submitted_at":"2023-12-03T16:58:10Z","title":"D-Bot: Database Diagnosis System using Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.01454","snapshot_observed_at":"2026-08-11T18:18:35.186544Z","title":"D-bot: Database diagnosis system using large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.186544Z"},"links":{"cited_paper":"/paper/2312.01454","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:de0a2b3cf51c8d82d6dc4085b9dbf6505d3b063c6dc25d931c01854e169ae3fd","observation_id":"abadbec9-e5cf-45a2-a5d5-98c5f3caac9e","resolution":{"observed_at":"2026-08-11T18:18:35.186544Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.03157","last_updated":"2024-11-29T12:33:45Z","snapshot_observed_at":"2026-08-13T05:32:06.767783Z","submitted_at":"2023-11-06T14:52:30Z","title":"GPTuner: A Manual-Reading Database Tuning System via GPT-Guided Bayesian Optimization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.03157","snapshot_observed_at":"2026-08-11T18:18:35.192752Z","title":"Gptuner: A manual-reading database tuning system via gpt-guided bayesian optimization,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.192752Z"},"links":{"cited_paper":"/paper/2311.03157","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:22560a77ec069fe94756322c6bdefcd3b269f5677611a1d357e4f699f55547d3","observation_id":"36185ef6-0778-49d8-b497-72cfe3e0d94b","resolution":{"observed_at":"2026-08-11T18:18:35.192752Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.866302Z","title":"Finqa: A training-free dynamic knowledge graph question answering system in finance with llm-based revision,","venue":null,"work_id":"5631e072-fb00-4544-9eb2-ab7ef1b73e6d","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.198903Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:03299ef4dd8e2bfeef2a7bb3db5bbbea5b9fb4d6f9bde9681f1159f0599a79f7","observation_id":"850af4ad-def4-4e3d-8ef9-ac46b9eae680","resolution":{"observed_at":"2026-08-11T18:18:36.872536Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2212.10560","last_updated":"2023-05-25T23:50:07Z","snapshot_observed_at":"2026-08-15T15:06:42.719366Z","submitted_at":"2022-12-20T18:59:19Z","title":"Self-Instruct: Aligning Language Models with Self-Generated Instructions","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2212.10560","snapshot_observed_at":"2026-08-11T18:18:35.204614Z","title":"Self-instruct: Aligning language models with self- generated instructions,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.204614Z"},"links":{"cited_paper":"/paper/2212.10560","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:31c66996b0453d946210840a525fa398bcbbfa23eb47337cd4473c4ff651e288","observation_id":"15513920-055f-4112-9681-b4a9293b9893","resolution":{"observed_at":"2026-08-11T18:18:35.204614Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10035","last_updated":"2023-10-16T03:40:03Z","snapshot_observed_at":"2026-08-13T05:48:52.208434Z","submitted_at":"2023-10-16T03:40:03Z","title":"Empirical Study of Zero-Shot NER with ChatGPT","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10035","snapshot_observed_at":"2026-08-11T18:18:35.211982Z","title":"Empirical study of zero-shot ner with chatgpt,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.211982Z"},"links":{"cited_paper":"/paper/2310.10035","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:67a3f94767e02c7f88e83bba2b9af08695d738c176d6e88b93a4a2ca0be1a663","observation_id":"53b82de6-6fe6-4d5e-807c-7fdabd828fb3","resolution":{"observed_at":"2026-08-11T18:18:35.211982Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.847887Z","title":"Chinese ner using multi-view transformer,","venue":null,"work_id":"a8ae0261-c1f8-42d2-ad9f-a15630601b6f","year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.218498Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:ddf6305aadf582d50112fdebfd03b988b2836bd1bfe56a64e7f5e0b5ebb1a473","observation_id":"6433816b-f98e-45b2-9948-6727aea49204","resolution":{"observed_at":"2026-08-11T18:18:36.853314Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.17617","last_updated":"2024-10-31T07:23:09Z","snapshot_observed_at":"2026-08-13T15:50:37.519850Z","submitted_at":"2023-12-29T14:25:22Z","title":"Large Language Models for Generative Information Extraction: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.17617","snapshot_observed_at":"2026-08-11T18:18:35.224392Z","title":"Large language models for generative information extraction: A survey,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.224392Z"},"links":{"cited_paper":"/paper/2312.17617","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:1bc5103b1b6be4e3ef90cf4f5372c7b252e386d8122e06f3d6fa4c85a41fbda9","observation_id":"199d8fd7-17a1-4858-bfe3-bedde2ea0a90","resolution":{"observed_at":"2026-08-11T18:18:35.224392Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.706467Z","title":"Locality-sensitive hashing scheme based on p-stable distributions,","venue":null,"work_id":"02337e70-23be-42d3-a819-c90a198d7d2b","year":2004},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.230830Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:4d200f26c6719413e4730df915aba4e67db24c86112409e3f3bceebbe4dba983","observation_id":"f67bae77-ba05-430e-a136-40990ef34d71","resolution":{"observed_at":"2026-08-11T18:18:36.783454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-11T18:18:35.237373Z","title":"Parameter-efficient fine-tuning of large- scale pre-trained language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.237373Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:371820d5ff192c08795cb3046037367fe898808bcf2cb6fd79d0fe9bb3122f0c","observation_id":"89c6b0f5-5fe0-4b9c-a9b6-789ceb9fe718","resolution":{"observed_at":"2026-08-11T18:18:35.237373Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.613004Z","title":"On the effectiveness of parameter-efficient fine-tuning,","venue":null,"work_id":"1ec90c12-8557-42e3-9128-edab871e1315","year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.243519Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:3d4e6e74c0bd07282c6fa25013069d0732ddd42362fc8d83f5e1f9f624b11dfd","observation_id":"cb4dbb74-d6f4-41d1-adcb-eef436440e25","resolution":{"observed_at":"2026-08-11T18:18:36.681279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-11T18:18:35.307607Z","title":"Qlora: Efficient finetuning of quantized llms,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.307607Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:91f9731645aa37cc6a2bc6953e2ac19367a0511b315bc504ed09b70b119385fc","observation_id":"73d9f2b1-1150-481d-b22c-069f756c1377","resolution":{"observed_at":"2026-08-11T18:18:35.307607Z","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":"2026-08-11T18:18:35.491375Z","title":"Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning,","venue":null,"work_id":null,"year":1950},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.491375Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:bf098e7022bfdcd2623a5bddfa7bd75f4383539b86e4cf6d635ad234c04f0fef","observation_id":"fb982168-a8db-41ad-b826-64c300a1e819","resolution":{"observed_at":"2026-08-11T18:18:35.491375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-11T18:18:35.496476Z","title":"Lora: Low-rank adaptation of large language models,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.496476Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:45f4901fbf0edd29b8ddefea7f42e792bd8d0339bda2217a7b47c25adf4747b2","observation_id":"d85cf07f-25ba-4747-92f8-e397141fc490","resolution":{"observed_at":"2026-08-11T18:18:35.496476Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11242","last_updated":"2025-03-18T02:12:21Z","snapshot_observed_at":"2026-08-14T21:39:22.687723Z","submitted_at":"2023-12-18T14:40:20Z","title":"MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11242","snapshot_observed_at":"2026-08-11T18:18:35.506927Z","title":"Mac-sql: Multi-agent collaboration for text-to-sql,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.506927Z"},"links":{"cited_paper":"/paper/2312.11242","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:a0d3ffb04dd5abf8eb93cf33c4f79fc7bd2474391ed1f68a1ea7db90ffce7781","observation_id":"9eb562dd-e23e-4e91-a0a0-661afae7b262","resolution":{"observed_at":"2026-08-11T18:18:35.506927Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2405.16755","last_updated":"2024-11-25T19:43:07Z","snapshot_observed_at":"2026-08-14T05:58:28.233874Z","submitted_at":"2024-05-27T01:54:16Z","title":"CHESS: Contextual Harnessing for Efficient SQL Synthesis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2405.16755","snapshot_observed_at":"2026-08-11T18:18:35.512950Z","title":"Chess: Contextual harnessing for efficient sql synthesis,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.512950Z"},"links":{"cited_paper":"/paper/2405.16755","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:1e8d94169f5d439dc25adc35d9ff98c1af03d734debdc82d4fee8bb29e4bfef4","observation_id":"ddb585e4-330f-4e00-b217-aa14af94db18","resolution":{"observed_at":"2026-08-11T18:18:35.512950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-11T18:18:36.570645Z","title":"Natural language query for technical knowledge graph navigation,","venue":null,"work_id":"cc380ea5-ba1b-4019-a0c5-99e9d62c4441","year":2022},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.518952Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:f1509f9ad5c64634df19eecd4830688f76127a740f2e27ed71a292cb8bd46d9e","observation_id":"e4bf2e15-5b1a-44fc-8ee6-a299d36140f4","resolution":{"observed_at":"2026-08-11T18:18:36.577856Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1601.01280","last_updated":"2016-06-06T21:06:55Z","snapshot_observed_at":"2026-08-15T14:10:33.189287Z","submitted_at":"2016-01-06T19:13:12Z","title":"Language to Logical Form with Neural Attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1601.01280","snapshot_observed_at":"2026-08-11T18:18:35.523992Z","title":"Language to logical form with neural atten- tion,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.523992Z"},"links":{"cited_paper":"/paper/1601.01280","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:05537f0f8ff15605704740636363304bbe14130c5214889f23e50a8a4820b2cd","observation_id":"4d6f669c-960e-4f20-aa2f-a05d3873b67b","resolution":{"observed_at":"2026-08-11T18:18:35.523992Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1603.06393","last_updated":"2016-06-08T13:53:21Z","snapshot_observed_at":"2026-08-14T22:05:11.185899Z","submitted_at":"2016-03-21T11:35:08Z","title":"Incorporating Copying Mechanism in Sequence-to-Sequence Learning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1603.06393","snapshot_observed_at":"2026-08-11T18:18:35.529407Z","title":"Incorporating copying mechanism in sequence-to-sequence learning,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.529407Z"},"links":{"cited_paper":"/paper/1603.06393","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:bf17b170fae60b62ec80b263b0a1559b1644fcabda754b9cc931adc6ec01ae52","observation_id":"9c4f8a2e-6c12-41ea-bbf8-5fd1c67c7313","resolution":{"observed_at":"2026-08-11T18:18:35.529407Z","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":"2026-08-11T18:18:35.534389Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.534389Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:6160ed1a1253afbc4dfc537db94556246d09a8a05bd16e74563e818d79b159b0","observation_id":"6d66109e-7220-44d9-ae77-b0eaffa87d4f","resolution":{"observed_at":"2026-08-11T18:18:35.534389Z","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":"2026-08-11T18:18:35.539113Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.539113Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:971e5dd8ab748d8aa23c4b8bb902c9071b2d0fa74ae45eb2d233d48d6eb50193","observation_id":"1ccfcbbe-edb3-405c-8a59-66189ea63686","resolution":{"observed_at":"2026-08-11T18:18:35.539113Z","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":"2026-08-11T18:18:35.544795Z","title":"Language models are unsupervised multitask learners,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.544795Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:13f4b1a889a7969989940b466f39c7210de99f61409c7491f472b373757760c4","observation_id":"37a0b956-aa57-4339-89a7-c0cb5171a136","resolution":{"observed_at":"2026-08-11T18:18:35.544795Z","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":"2026-08-11T18:18:35.551069Z","title":"Chase-sql: Multi-path reasoning and preference optimized candidate selection in text-to-sql,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.551069Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:d4a90370606e6fd5573ff8777c6f90e76598b85563922293c0f3faa6ffe9df10","observation_id":"fcffd359-0167-40a2-a902-48d6ce88ecbf","resolution":{"observed_at":"2026-08-11T18:18:35.551069Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.07702","last_updated":"2024-08-18T19:06:04Z","snapshot_observed_at":"2026-08-12T23:03:32.635415Z","submitted_at":"2024-08-14T17:59:04Z","title":"The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.07702","snapshot_observed_at":"2026-08-11T18:18:35.563469Z","title":"The death of schema linking? text-to-sql in the age of well-reasoned language models,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.563469Z"},"links":{"cited_paper":"/paper/2408.07702","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:35a01d0185690dd149d46ce4f767919ccdabef46097ef05a648afd036ae6a01b","observation_id":"2745635c-fc26-4527-afbc-97d617ec5b3f","resolution":{"observed_at":"2026-08-11T18:18:35.563469Z","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":"2026-08-11T18:18:35.703463Z","title":"Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.703463Z"},"links":{"citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:c9d8571204d0b9f89a2a008541fb2fc194429c1c5e55b1d21029b647984d9b13","observation_id":"60946983-411d-4493-8fbe-90fa95f39e87","resolution":{"observed_at":"2026-08-11T18:18:35.703463Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.16751","last_updated":"2025-01-28T09:45:41Z","snapshot_observed_at":"2026-08-12T22:37:57.931157Z","submitted_at":"2024-09-25T09:02:48Z","title":"E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQL","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.16751","snapshot_observed_at":"2026-08-11T18:18:35.823544Z","title":"E-sql: Direct schema linking via question enrichment in text-to-sql,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.823544Z"},"links":{"cited_paper":"/paper/2409.16751","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:9be9adb928c29d8c266c9bc0765c1341bfc898de9b7aaa010d32d608019c116e","observation_id":"daa0dc7f-c39f-4168-8642-f29de406eb89","resolution":{"observed_at":"2026-08-11T18:18:35.823544Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2105.11644","last_updated":"2021-05-25T03:45:30Z","snapshot_observed_at":"2026-08-12T13:11:36.780908Z","submitted_at":"2021-05-25T03:45:30Z","title":"A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2105.11644","snapshot_observed_at":"2026-08-11T18:18:35.831633Z","title":"A survey on complex knowledge base question answering: Methods, challenges and solutions,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.831633Z"},"links":{"cited_paper":"/paper/2105.11644","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:7c0d667ddee219795dcdb9e1afa2214e13e2c1a66330dbe3a98342f531723a0c","observation_id":"44cec781-c011-4754-aad6-0a0d4f32d47f","resolution":{"observed_at":"2026-08-11T18:18:35.831633Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.01943","last_updated":"2024-10-02T18:41:35Z","snapshot_observed_at":"2026-08-15T04:16:40.315270Z","submitted_at":"2024-10-02T18:41:35Z","title":"CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.01943","snapshot_observed_at":"2026-08-11T18:18:35.557453Z","title":"Available: https://arxiv.org/abs/2410.01943","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-11T18:18:35.557453Z"},"links":{"cited_paper":"/paper/2410.01943","citing_paper":"/paper/2412.10434"},"observation_digest":"sha256:18c966c980afafa1301cb8fcae53cdccccfca856cc767525944cdcbf4d02e2fb","observation_id":"2afc5e14-9046-4ceb-9584-bf667afe81aa","resolution":{"observed_at":"2026-08-11T18:18:35.557453Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.10434","last_updated":"2024-12-11T04:14:09Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-15T17:54:44.098173Z","submitted_at":"2024-12-11T04:14:09Z","title":"NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":26,"verified_exact":0,"verified_fuzzy":16},"total_outbound_references":42},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 15 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2412.10434."}