{"as_of":"2026-08-13T15:31:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:1697481f4444b5af31d1139ab9fc34d845a3a437279117b896a920e332eccd10","coverage":[{"denominator":28,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":28,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-11T22:38:57.361516Z","state":"measured"},{"denominator":28,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":28,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-13T06:32:02.005865+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/2412.03270/citation-record","integrity":"/paper/2412.03270/integrity","json":"/paper/2412.03270/citation-record.json","paper":"/paper/2412.03270"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.18013","last_updated":"2025-08-15T03:28:39Z","snapshot_observed_at":"2026-08-13T04:08:37.953823Z","submitted_at":"2024-02-28T03:16:44Z","title":"A Survey on Recent Advances in LLM-Based Multi-turn Dialogue Systems","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.18013","snapshot_observed_at":"2026-08-11T22:38:55.956088Z","title":"A Survey on Recent Ad- vances in LLM-Based Multi-turn Dialogue Systems[J]","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:55.956088Z"},"links":{"cited_paper":"/paper/2402.18013","citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:f43b1f8d6ad77ac01299ccceda5bb8e70cc8a71bfc05ef7cd2eb2ab4a0d49680","observation_id":"ee508d99-ddd7-44ec-8185-1ad24e160fe5","resolution":{"observed_at":"2026-08-11T22:38:55.956088Z","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":"2026-08-11T22:38:59.632386Z","title":null,"venue":null,"work_id":"dcfaae49-881c-420e-ace7-c93f73ec70cd","year":null},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.134761Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:db953cebe6ccb57b3ced40b009ec3b067340d3207777f60e2f963bc92ee2114f","observation_id":"59e871eb-2385-4a3c-9c5d-ebe1c3a46f12","resolution":{"observed_at":"2026-08-11T22:38:59.697364Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:56.270238Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.270238Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:c89bdbf568afc0a77d28da2d480e40b72a8fd2ecb0191e9fdc8bc5415329e822","observation_id":"f27d0dfb-8ddc-419f-9563-cadcf66c4d16","resolution":{"observed_at":"2026-08-11T22:38:56.270238Z","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":"2026-08-11T22:38:59.565253Z","title":null,"venue":null,"work_id":"9e2698bf-e989-49f0-b718-fa74ca09faa4","year":2022},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.324872Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:466a22e6907963817d5a2f0b649f12bf3dcdf6ec30103370f813e3f41c6e51e8","observation_id":"f16c213d-bc10-4c26-a1d2-c1cde5c2f8b7","resolution":{"observed_at":"2026-08-11T22:38:59.579402Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:59.504815Z","title":"Language models are few-shot learners[C]//Proceedings of the 34th International Conference on Neural Information Processing Systems","venue":null,"work_id":"f6be6264-49c8-433b-81d2-0b48fd9fc33c","year":2020},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.354757Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:bc269526f8467c9a5d32212b535b11699bb173afd08f53744ecacab983c8c7b8","observation_id":"f86bed9e-ddfb-47d6-8daa-4fb3ca8c8e40","resolution":{"observed_at":"2026-08-11T22:38:59.513517Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:59.463222Z","title":null,"venue":null,"work_id":"10789a58-714d-4606-a0e3-cd191ad0d6b3","year":2024},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.400662Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:372e18c68596ad739a774f93f727331ed8ca15e56c1f4dc932376d00fe5be873","observation_id":"8b0738e2-6d7d-475b-a3a1-0963d99ec15c","resolution":{"observed_at":"2026-08-11T22:38:59.483914Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:56.440633Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.440633Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:5cafcb31bf49bb79aed66f650e3ca194a42787a34b36f9f083444e28482f1eba","observation_id":"5c60613f-14b0-4e60-8388-2dc2653a8f57","resolution":{"observed_at":"2026-08-11T22:38:56.440633Z","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":"2026-08-11T22:38:56.454869Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.454869Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:2fd26619b237fe20e9aa2c7006c194e4ac78e185e954810d326e37ae8b9c6689","observation_id":"025b7dae-27e9-4062-91ad-5abf6f5ceefa","resolution":{"observed_at":"2026-08-11T22:38:56.454869Z","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":"2026-08-11T22:38:59.421019Z","title":null,"venue":null,"work_id":"e8ff46d0-b316-480d-9e25-586891806eee","year":2024},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.494760Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:8cb3faffc561e405c6ec348dead33b692d7cbe9eb7a626bb6f67a73b455beafb","observation_id":"a4ab1901-c4a9-42fc-be0e-72fe6140d396","resolution":{"observed_at":"2026-08-11T22:38:59.437824Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2309.05922","last_updated":"2023-09-12T02:34:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-12T02:34:06Z","title":"A Survey of Hallucination in Large Foundation Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.05922","snapshot_observed_at":"2026-08-11T22:38:56.614760Z","title":"A survey of hallucination in large foundation models[J]","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.614760Z"},"links":{"cited_paper":"/paper/2309.05922","citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:78e76c7f13417686d3263041ff45cadd9b34f020488a8bbe0bd6bf1035026332","observation_id":"9b08dc1a-b496-41b5-b260-e9a0ada554ab","resolution":{"observed_at":"2026-08-11T22:38:56.614760Z","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":"2026-08-11T22:38:59.305156Z","title":"Smith, and Mari Ostendorf","venue":null,"work_id":"6a88b25a-7dc6-4afa-adce-b293000671bc","year":2022},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.717266Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:ff4349145ad749e978a718ce01fa5b39c8560e585980df3e6584fb7a524fc68f","observation_id":"2388e5ed-4cd4-47d1-a8e6-4e770fb27e69","resolution":{"observed_at":"2026-08-11T22:38:59.334731Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:59.165093Z","title":null,"venue":null,"work_id":"f932f395-91cd-47aa-84ae-349321bb0a11","year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.767951Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:005a3b7df9e843ca414f78ebbcb38e16439e198c604231f7a7cd019872ea5fdd","observation_id":"87061d01-927d-4977-93c2-89c04e4a6d86","resolution":{"observed_at":"2026-08-11T22:38:59.241726Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:59.054697Z","title":"Exploring the limits of transfer learning with a unified text-to-text transformer[J]","venue":null,"work_id":"32f874e1-7361-4bb8-a96d-4f6cfe714b48","year":2020},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.784892Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:1679d3f7a3ffb7d250c0f17437d3c09d8472be3aabcf7de459bdc9543abbee08","observation_id":"9657887a-4c80-4218-89da-89bbe4eadbd3","resolution":{"observed_at":"2026-08-11T22:38:59.100405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:59.013072Z","title":null,"venue":null,"work_id":"584a47a2-0096-4f5c-8a72-a37ca5a2030b","year":2018},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.834758Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:8112360c5c1818f5f39dbe937af1bbdfbc7d614b7421b05c7ed43cfccbc8403f","observation_id":"e4bbecea-dd18-4e27-bfb8-2973f5f22e11","resolution":{"observed_at":"2026-08-11T22:38:59.025015Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.964946Z","title":null,"venue":null,"work_id":"9bdd624b-0591-4e1e-bdd9-41e0c6bee5e2","year":2022},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.882901Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:67c69e542def4024d46f5e9a8420df49edf7ea4b7f2bf25dae772c185852a680","observation_id":"05aea17c-211c-4a93-816d-405177871556","resolution":{"observed_at":"2026-08-11T22:38:58.976070Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.911499Z","title":"Word-based dialog state tracking with recurrent neural networks[C]//Proceedings of the 15th annual meet- ing of the special interest group on discourse and dialogue (SIGDIAL)","venue":null,"work_id":"412203ae-e7b5-46f1-9294-45891d1033e2","year":2014},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.934848Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:bb6b029f3a8632ed1ea6149fbe877ce0a0491a58ed32a2361d21c7eea013b4ab","observation_id":"2d523481-d18c-4063-813a-8aa76b00e27f","resolution":{"observed_at":"2026-08-11T22:38:58.922034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.847120Z","title":null,"venue":null,"work_id":"56b939b7-2121-4cc7-af0b-e39d306f7b74","year":2019},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.995913Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:6edc0db803b18ba8c8d0796856b01dcb3e501de106631d4240e2e9df45060e7f","observation_id":"ccad8e72-3a8e-4d95-a147-95f430c1f059","resolution":{"observed_at":"2026-08-11T22:38:58.874754Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.12950","last_updated":"2024-01-31T19:47:26Z","snapshot_observed_at":"2026-08-13T04:25:38.282910Z","submitted_at":"2023-08-24T17:39:13Z","title":"Code Llama: Open Foundation Models for Code","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.12950","snapshot_observed_at":"2026-08-11T22:38:57.034764Z","title":"Code llama: Open foundation models for code[J]","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.034764Z"},"links":{"cited_paper":"/paper/2308.12950","citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:369f0ccaa2d589195bad2a2b3da2548977037fedb28a10431a2c2ec7becd56ee","observation_id":"51a5578f-3ca2-4b4f-8dcf-4aee7632665b","resolution":{"observed_at":"2026-08-11T22:38:57.034764Z","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":"2026-08-11T22:38:58.727293Z","title":null,"venue":null,"work_id":"aae3c854-1cb4-4aae-a6a1-84300e3e441f","year":2019},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.135086Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:669d4c96e0825f26153007d74f397a487a26cbba6b0cecfa9acf08d0e3764154","observation_id":"c186375b-8e75-44d7-8e33-c77d8e0d4132","resolution":{"observed_at":"2026-08-11T22:38:58.739788Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.691551Z","title":"Dialogue State Tracking with a Language Model using Schema-Driven Prompting[C]//Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing","venue":null,"work_id":"7a12af30-94c7-4347-80e7-3857e70f1988","year":2021},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.224754Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:3918653459164b3fe9618e08a85453d841d48753e68c3103e66aca784ced305d","observation_id":"dfdc99a6-2224-4a11-977e-4712c452f44a","resolution":{"observed_at":"2026-08-11T22:38:58.711480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.634478Z","title":null,"venue":null,"work_id":"a0c5e3c5-dcde-4be2-96ce-02c0a2a13d3b","year":2022},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.250338Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:bd274b10a7114735c3b54a842b2704467cbaa2e8865c0e447cb30ee4e86ed8bc","observation_id":"79a6d599-78a1-4d4f-a494-f6733beeecaf","resolution":{"observed_at":"2026-08-11T22:38:58.654783Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:57.267439Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.267439Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:b659a6594e20ef0b1f474fe6c35c5325a5cd5157232de559b86ebbeda9150040","observation_id":"799ecf63-1bc6-45e5-a29a-ee796e2669f8","resolution":{"observed_at":"2026-08-11T22:38:57.267439Z","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":"2026-08-11T22:38:58.562337Z","title":null,"venue":null,"work_id":"a144158e-50ed-4e1b-bfb1-f0470330a60b","year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.301982Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:7c23ad9c4efd0917c7b169169880bb41df73c317aaacba271d452bdf2a4d7193","observation_id":"f6a62c1b-1ae2-4378-a12a-3df71c5401e3","resolution":{"observed_at":"2026-08-11T22:38:58.611752Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.491604Z","title":"Towards LLM-driven Dialogue State Tracking[C]//Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing","venue":null,"work_id":"3f450eb2-a4af-474b-83bd-8b1be4d607d3","year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.328433Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:8151ed5ba5f30daa564f199cc464a693fb00797e30f78c6fffc77107dcf58b22","observation_id":"5b8eb393-efb8-4695-99c1-3ca8b3787434","resolution":{"observed_at":"2026-08-11T22:38:58.521906Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.360025Z","title":"Building Multi-domain Dialog State Trackers from Single-domain Dialogs[C]//Proceedings of the 2023 Con- ference on Empirical Methods in Natural Language Processing","venue":null,"work_id":"7f354805-80ab-4ad9-bd19-6a826b492d7f","year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.333767Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:beb953a33327b05ed82f3c8253528c058fa140be811000a40a96d100d4ae8292","observation_id":"30a24cbe-6e95-45ba-8e4e-3fc8e58563f6","resolution":{"observed_at":"2026-08-11T22:38:58.402290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.277394Z","title":null,"venue":null,"work_id":"4bc767b9-0b5a-4097-bad4-922417b5ecf2","year":2022},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.353860Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:1fd3b39334c8d0ce333919cf52eb12ec0ab8bb943b2e0fd5e75e5c965c8a632a","observation_id":"37135db6-b1b7-4fd1-ad1e-a4e4c06e02a7","resolution":{"observed_at":"2026-08-11T22:38:58.297862Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:58.211820Z","title":"TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking[C]//Proceedings of the 21th Annual Meeting of the Special Interest Group on Discourse and Dialogue","venue":null,"work_id":"bb45ff8a-199a-4f3b-8eb4-399919f2b0e6","year":2020},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:57.361516Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:b19ad25b2287825d775dde44959d1f1519856d2a7965212945e9f83db207bc56","observation_id":"32dda6a1-9307-4e74-b175-14bbfe44ab30","resolution":{"observed_at":"2026-08-11T22:38:58.229199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+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":"2026-08-11T22:38:56.151849Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking","version":1},"reference_index":2022,"source":"pdf_text","source_observed_at":"2026-08-11T22:38:56.151849Z"},"links":{"citing_paper":"/paper/2412.03270"},"observation_digest":"sha256:ec7807b13fb0d3c92d14e1f0832d9fc2c377e3808c346930116ad3d1fbe9162a","observation_id":"c3c9afb0-c3af-49f2-bd09-8aa02a05925f","resolution":{"observed_at":"2026-08-11T22:38:56.151849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2412.03270","last_updated":"2024-12-04T12:25:41Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-12T05:31:44.116144Z","submitted_at":"2024-12-04T12:25:41Z","title":"Intent-driven In-context Learning for Few-shot Dialogue State Tracking"},"reference_resolution":{"displayed":28,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":20,"verified_exact":0,"verified_fuzzy":8},"total_outbound_references":28},"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":"2026-08-13T06:32:02.005865+00:00","source":"crossref"},{"observed_at":"2026-08-13T06:31:53.387327+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 0 inbound Pith citation observations for arXiv:2412.03270."}