{"as_of":"2026-08-24T01:26:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:179f9361638b2d54b67d05616c0dbb2713e0cfbf94ab1b721d8f72694979d18c","coverage":[{"denominator":29,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":29,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T16:26:26.009741Z","state":"measured"},{"denominator":29,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":29,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-23T06:30:58.430688+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2507.13544/citation-record","integrity":"/paper/2507.13544/integrity","json":"/paper/2507.13544/citation-record.json","paper":"/paper/2507.13544"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1706.03762","last_updated":"2023-08-02T00:41:18Z","snapshot_observed_at":"2026-08-19T04:42:40.974785Z","submitted_at":"2017-06-12T17:57:34Z","title":"Attention Is All You Need","version":7},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03762","snapshot_observed_at":"2026-08-06T16:26:23.591335Z","title":"N., Kaiser, Ł., & Polosukhin, I","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.591335Z"},"links":{"cited_paper":"/paper/1706.03762","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:fb9ba337565078a03328350dfcf4b68cbd7bddeda6889a6a7b1783742d7ac2f7","observation_id":"b081de3e-44b3-495c-9776-febd3bab196d","resolution":{"observed_at":"2026-08-06T16:26:23.591335Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:28.997771Z","title":null,"venue":null,"work_id":"7980d890-98c4-4e90-8055-117a2e7e4a9c","year":2018},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.663858Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:c64c064593957e356ad0ffa183d1ffc11c83ee0f66af7335a90eab0e6ae1760c","observation_id":"0f29806a-15b2-486d-aae1-74eea66f995c","resolution":{"observed_at":"2026-08-06T16:26:29.029827Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.18223","last_updated":"2026-03-18T05:34:39Z","snapshot_observed_at":"2026-08-14T10:40:26.323157Z","submitted_at":"2023-03-31T17:28:46Z","title":"A Survey of Large Language Models","version":19},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.18223","snapshot_observed_at":"2026-08-06T16:26:23.730958Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.730958Z"},"links":{"cited_paper":"/paper/2303.18223","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:82b51bc2e441a4f1e5331d965bafc40d395adc65f35be7e98bcff22c8b29edfa","observation_id":"b877d28e-6012-408b-9fda-694cf60fbe24","resolution":{"observed_at":"2026-08-06T16:26:23.730958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:28.776598Z","title":"Natural Language Processing Advancements: Breaking Barriers in Human-Computer Interaction,","venue":null,"work_id":"fe15d007-3459-42bb-8784-650a449a2c6b","year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.808393Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:236f7af53a62d1743197a04382cda68b59d0e18aa31eeea618e13c065182425c","observation_id":"f430696a-9ba5-46e7-989a-e4d86ae75493","resolution":{"observed_at":"2026-08-06T16:26:28.886316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:23.938669Z","title":"Cross-lingual Transfer Learning for Multilingual Task Oriented Dialogue","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.938669Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:c3c94c7864e5cc1a2cc0b925d35291e1925147a451e16f4283a84d17257e7aed","observation_id":"c9c57e28-effb-4bd5-a844-54a34cf2dbb2","resolution":{"observed_at":"2026-08-06T16:26:23.938669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:28.587078Z","title":"Dialogue Act Classi- fication in Domain-Independent Conversations Using a Deep Recurrent Neural Network,","venue":null,"work_id":"4ccaebe5-4e6d-442a-adac-9a529b0f628a","year":2016},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:23.995867Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:e8163d9635c553b655f9a5bb9ea488ace67841ac8d9c92da8a715ff299d3a32a","observation_id":"b65a4e79-64ee-4ecd-a36b-acc33daf78ab","resolution":{"observed_at":"2026-08-06T16:26:28.691590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:28.400841Z","title":"Long Short-Term Memory,","venue":null,"work_id":"857831c3-538b-4b4d-90b3-c8a1864b1e09","year":1997},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.143937Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:08acc92add06c656863b164a9504087da06b6999e43395a78f1028bbb830100e","observation_id":"c5f75560-d218-4d4b-a7a5-3b44fbfebfb4","resolution":{"observed_at":"2026-08-06T16:26:28.496258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1508.01991","last_updated":"2015-08-09T06:32:47Z","snapshot_observed_at":"2026-08-19T21:29:59.580672Z","submitted_at":"2015-08-09T06:32:47Z","title":"Bidirectional LSTM-CRF Models for Sequence Tagging","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1508.01991","snapshot_observed_at":"2026-08-06T16:26:24.218723Z","title":"Bidirectional LSTM-CRF Models for Sequence Tagging,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.218723Z"},"links":{"cited_paper":"/paper/1508.01991","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:0327dd08cfb1174aff2ff6fc2b77e9f7482500e1fd03f5574f17dcd86334d097","observation_id":"67e0acb1-2013-46fb-b55b-f7f8ae9841db","resolution":{"observed_at":"2026-08-06T16:26:24.218723Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:28.217949Z","title":"In Proceedings of the 23rd International Conference on Hybrid Intelligent Systems (HIS 2023) , 2023","venue":null,"work_id":"0e6913fd-68e3-4c74-9955-768ce7876b0a","year":2023},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.352166Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:bad3435eb220dedf5cb96970924610f6a39caa5b289207df3cfc4102101bd201","observation_id":"ee449d51-daf5-4102-bd40-532e48f5e5b3","resolution":{"observed_at":"2026-08-06T16:26:28.292653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:28.054320Z","title":"spaCy 2: Natural Language Under- standing with Bloom Embeddings, Convolutional Neural Networks, and Incremental Parsing,","venue":null,"work_id":"819b8973-d520-4137-8b43-0c80fad7df0d","year":2017},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.452318Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:ce14931083d53dd5bf4cbf9dbbfb95655f86e46ccb4934f7c151056c743bcc62","observation_id":"a3af78fd-cbdb-4fd7-9311-0562b29064d1","resolution":{"observed_at":"2026-08-06T16:26:28.117227Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1908.10084","last_updated":"2019-08-27T08:50:17Z","snapshot_observed_at":"2026-08-14T05:02:11.716316Z","submitted_at":"2019-08-27T08:50:17Z","title":"Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1908.10084","snapshot_observed_at":"2026-08-06T16:26:24.554804Z","title":"Sentence-BERT: Sentence Embeddings Using Siamese BERT-Networks,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.554804Z"},"links":{"cited_paper":"/paper/1908.10084","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:b9e7c05c27c9724ea8668efcf704008f093641a7288e0d27a317bd2d15e971ad","observation_id":"0cdfc4f9-5933-400c-987d-e6849de20e02","resolution":{"observed_at":"2026-08-06T16:26:24.554804Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.863207Z","title":null,"venue":null,"work_id":"7f917bef-ba4b-409c-834b-5503188adab5","year":2007},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.659728Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:b7bb23fee2accbf1c2bbe3ac2e543bfa10b4dfe6809270135eb9fd3967bdcdcb","observation_id":"af812956-024e-4cd3-ab52-5bd5c7985be9","resolution":{"observed_at":"2026-08-06T16:26:27.954810Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.10670","last_updated":"2024-11-16T02:16:59Z","snapshot_observed_at":"2026-08-17T14:18:18.096968Z","submitted_at":"2024-11-16T02:16:59Z","title":"IntentGPT: Few-shot Intent Discovery with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.10670","snapshot_observed_at":"2026-08-06T16:26:24.746843Z","title":"IntentGPT: Few-shot Intent Discovery with Large Language Models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.746843Z"},"links":{"cited_paper":"/paper/2411.10670","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:c373fcb2a35957adff30f0e3580bece9e93e58d9e01246437133b466870f67bd","observation_id":"3b7ede4f-00c5-43f9-9102-a29720c2a83b","resolution":{"observed_at":"2026-08-06T16:26:24.746843Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.689450Z","title":null,"venue":null,"work_id":"769150f1-f654-4e14-95cd-e42a8a9da5a0","year":2023},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.827100Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:c4372bc89f9dc00151fac5e0158975c5208283e55a58ad3abcf523041d760fa5","observation_id":"0ae7a629-183c-4c33-a24e-826e6e18a05e","resolution":{"observed_at":"2026-08-06T16:26:27.759492Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2305.13512","last_updated":"2023-08-17T19:23:20Z","snapshot_observed_at":"2026-08-19T18:01:00.974931Z","submitted_at":"2023-05-22T21:59:26Z","title":"Can ChatGPT Detect Intent? Evaluating Large Language Models for Spoken Language Understanding","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.13512","snapshot_observed_at":"2026-08-06T16:26:24.938493Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:24.938493Z"},"links":{"cited_paper":"/paper/2305.13512","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:efb9ea1cadf06be6658d36216b716845ff4fc0f405fd6827e0f604df292de2dd","observation_id":"91885723-a7a2-4472-9e7c-1dd81a4d4581","resolution":{"observed_at":"2026-08-06T16:26:24.938493Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.544361Z","title":"ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler","venue":null,"work_id":"625f0662-8249-429c-9a69-4007e11c5568","year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.015752Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:3e68e3710f87283f78e6336ddd088efd610df2f2e70b2c707001a74700caf135","observation_id":"1db44bc9-2411-4c1b-af51-2c0a8eea46bb","resolution":{"observed_at":"2026-08-06T16:26:27.603356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2410.22552","last_updated":"2024-10-29T21:37:04Z","snapshot_observed_at":"2026-08-17T19:13:15.897608Z","submitted_at":"2024-10-29T21:37:04Z","title":"Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.22552","snapshot_observed_at":"2026-08-06T16:26:25.147581Z","title":"Auto-Intent: Automated Intent Discovery and Self- Exploration for Large Language Model Web Agents","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.147581Z"},"links":{"cited_paper":"/paper/2410.22552","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:072674893b3969896029cef86be6fddd34940cbfba61748e4b6e2dae6db288bf","observation_id":"ed8307a7-1aa2-4894-95d2-b2e5792a3ae3","resolution":{"observed_at":"2026-08-06T16:26:25.147581Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.223647Z","title":"A rule-based short query intent identifi- cation system,","venue":null,"work_id":"50848195-2b40-46dd-8475-b6db71cd8d15","year":2010},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.241497Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:849ed8140f84f942961966192ede8238fb9ae6450d561765d8450e557825483a","observation_id":"7e6246b8-48b1-4df0-b1a6-acfdbb66181b","resolution":{"observed_at":"2026-08-06T16:26:27.308340Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:25.341680Z","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding,","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.341680Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:b3682226234fcc087e87475cc6dc8f642c4c17ebe003cef0fe4d8fdf417b3737","observation_id":"8456ceaf-c74e-4bcc-a3dd-e0a86e025cbd","resolution":{"observed_at":"2026-08-06T16:26:25.341680Z","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":"2026-08-06T16:26:25.407334Z","title":"KeyBERT: Minimal keyword extraction with BERT,","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.407334Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:541e157e3afd37621062e34ebc33bf91ed16fa0615e350b79b46ffaef03f42e4","observation_id":"548e2813-384a-45d9-9fa0-fc65081738b4","resolution":{"observed_at":"2026-08-06T16:26:25.407334Z","resolver_source":null,"status":"malformed_identifier"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.081496Z","title":"Intent Discovery Through Unsu- pervised Semantic Text Clustering,","venue":null,"work_id":"051c5b56-6fcc-410b-9897-77ac2e8ff9cd","year":2018},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.492954Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:b7db9c206d929b11186b720d642bf9029947066dee7f52e80ad9bd06f05d7465","observation_id":"83449ef3-e3a0-4a22-87a6-a348e442f896","resolution":{"observed_at":"2026-08-06T16:26:27.144630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05530","last_updated":"2024-12-16T17:39:39Z","snapshot_observed_at":"2026-08-14T18:15:53.516440Z","submitted_at":"2024-03-08T18:54:20Z","title":"Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05530","snapshot_observed_at":"2026-08-06T16:26:25.591629Z","title":"Gem- ini 1.5: Unlocking Multimodal Understanding Across Millions of Tokens of Context,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.591629Z"},"links":{"cited_paper":"/paper/2403.05530","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:5a71a949ae9982a381489fc9e94043c8db06d3597932d0adde1dda2e2179bd02","observation_id":"4c9fd5d1-2478-46ad-aef7-a102ffa607a7","resolution":{"observed_at":"2026-08-06T16:26:25.591629Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:26.890865Z","title":null,"venue":null,"work_id":"3cb7919c-8289-47c6-bb55-70cf4b257f0f","year":1998},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.661449Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:1d56811b18392223f144c6ca7b2ac34956432f8f47b38bfefa1f4091e31344b9","observation_id":"fde6d702-14d4-486c-8b71-f756cb26d8a8","resolution":{"observed_at":"2026-08-06T16:26:26.979097Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:26.749579Z","title":"On the number of cycles in a graph","venue":null,"work_id":"79a16424-347a-4a23-9f21-bece4407a9e9","year":1971},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.724533Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:4fa507e0254198ae5db2dab0fe947481362c98ab658fdb324f0abdc8a26d6796","observation_id":"23402a23-0179-4ccc-b7e4-fa087d7aad6c","resolution":{"observed_at":"2026-08-06T16:26:26.814992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:26.555601Z","title":"Gromov hyperbolic graphs,","venue":null,"work_id":"96fba705-1213-4bcf-b291-5c7008d8a92f","year":2013},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.795624Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:89ce6b4465707d37e40e9782ace4510c8ff3f7ad85ae7622b03b7011629497db","observation_id":"3e45b43e-7f1b-46df-afd3-58a710b2fad4","resolution":{"observed_at":"2026-08-06T16:26:26.660372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+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":"2026-08-06T16:26:25.867194Z","title":"On the Hyperbolicity of Small-World and Treelike Random Graphs,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.867194Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:e7a097dbef6e75fcc40f989cecd35f1494f9a2e61955c0758b479c3a98af18b2","observation_id":"3d6a03a3-ea1e-4fba-908c-365169a65ef4","resolution":{"observed_at":"2026-08-06T16:26:25.867194Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:26.424121Z","title":"MultiWOZ 2.2: A dialogue dataset with additional annotation corrections and state tracking baselines","venue":null,"work_id":"5bb3fe85-7f00-4718-a773-bc91ad80dc39","year":2020},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.960149Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:0d3f16e245311febb63ec0abd2440fb017879a08aeb07600ba9c9fc94e50abf4","observation_id":"6c2bce20-d2c1-4878-9af1-de06e0a2e08a","resolution":{"observed_at":"2026-08-06T16:26:26.465754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.00783","last_updated":"2021-04-01T22:04:25Z","snapshot_observed_at":"2026-08-16T18:34:21.964320Z","submitted_at":"2021-04-01T22:04:25Z","title":"Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.00783","snapshot_observed_at":"2026-08-06T16:26:26.009741Z","title":"Action- based conversations dataset: A corpus for building more in-depth task- oriented dialogue systems","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:26.009741Z"},"links":{"cited_paper":"/paper/2104.00783","citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:7f3ab6444bc0d16ea40474512eab9d46af048045cccad8acc3d0b22d123209ce","observation_id":"5fffe19c-2807-4e93-bff5-4d531380e7bc","resolution":{"observed_at":"2026-08-06T16:26:26.009741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T16:26:27.385756Z","title":null,"venue":null,"work_id":"b0f26a34-0896-4ac3-ae98-fd1b7bc078ea","year":2024},"citing_paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-06T16:26:25.086547Z"},"links":{"citing_paper":"/paper/2507.13544"},"observation_digest":"sha256:badd2a640afac1a29224c4b4322fd548d7afb210b14941f43ef68c3b9b32fd0a","observation_id":"8a68379d-7929-406e-85b9-f4228fdde4d8","resolution":{"observed_at":"2026-08-06T16:26:27.441199Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2507.13544","last_updated":"2025-07-17T21:34:13Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-21T05:23:32.182834Z","submitted_at":"2025-07-17T21:34:13Z","title":"A Computational Approach to Modeling Conversational Systems: Analyzing Large-Scale Quasi-Patterned Dialogue Flows"},"reference_resolution":{"displayed":29,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":0,"verified_fuzzy":11},"total_outbound_references":29},"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":"2026-08-23T06:30:58.430688+00:00","source":"crossref"},{"observed_at":"2026-08-23T06:30:53.778098+00:00","source":"retraction_watch"}],"thesis":"As of 24 August 2026, this Paper Citation Record lists 29 of 29 outbound references and 0 inbound Pith citation observations for arXiv:2507.13544."}