{"as_of":"2026-08-20T08:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3dbe2abf1239aa468f24f575f1b34a3329274e2f61daa320e0f07f9eece6646a","coverage":[{"denominator":23,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":23,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T01:03:12.430383Z","state":"measured"},{"denominator":23,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":23,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-20T06:33:59.587034+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/2505.02209/citation-record","integrity":"/paper/2505.02209/integrity","json":"/paper/2505.02209/citation-record.json","paper":"/paper/2505.02209"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T01:03:12.960187Z","title":"An Iterative Self- Learning Framework for Medical Domain Generalization","venue":null,"work_id":"c665186f-c85b-4eda-a3ad-a9a3095b8e1e","year":2023},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.319116Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:a7b4005a1d93e3bc731bb2a399893176bc900e9027d6184e7b4079c6b956b2b7","observation_id":"839a9b78-ab38-4208-819a-cdac1124408c","resolution":{"observed_at":"2026-08-16T01:03:12.965380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.08987","last_updated":"2021-03-22T02:35:17Z","snapshot_observed_at":"2026-08-19T13:11:14.995250Z","submitted_at":"2020-12-16T14:32:06Z","title":"Discovering New Intents with Deep Aligned Clustering","version":7},"cited_work":{"arxiv_id":"2012.08987","doi":null,"metadata_source":"pith","pith_arxiv_id":"2012.08987","snapshot_observed_at":"2026-08-16T01:03:12.743255Z","title":"Discovering New Intents with Deep Aligned Clustering","venue":"cs.CL","work_id":"09061258-a9fd-4979-b20a-1196d4a25d15","year":2020},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.324679Z"},"links":{"cited_paper":"/paper/2012.08987","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:0fa92db547d78f347cb4510a7d5b856d8eaeb498f0756581ad19926e0b89e81b","observation_id":"adf7b6eb-033c-49e4-8be6-1d73b22e51d8","resolution":{"observed_at":"2026-08-16T01:03:12.749061Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.12114","last_updated":"2021-12-14T01:53:19Z","snapshot_observed_at":"2026-08-19T13:11:16.074647Z","submitted_at":"2021-04-25T09:36:23Z","title":"Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing","version":2},"cited_work":{"arxiv_id":"2104.12114","doi":null,"metadata_source":"pith","pith_arxiv_id":"2104.12114","snapshot_observed_at":"2026-08-16T01:03:12.719915Z","title":"Open Intent Discovery through Unsupervised Semantic Clustering and Dependency Parsing","venue":"cs.CL","work_id":"bf70c73f-beab-4de6-9476-ef70f7a7c39e","year":2021},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.330082Z"},"links":{"cited_paper":"/paper/2104.12114","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:6794e1c5fefa439157998af8e270cc5cadd74c0303a5bcc7c0052bf203a2c87a","observation_id":"6374ac71-926b-4dbc-9314-fb32e90c4ba7","resolution":{"observed_at":"2026-08-16T01:03:12.725705Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.943831Z","title":"Supervised Clustering of Questions into Intents for Dialog System Applica- tions","venue":null,"work_id":"3418fe8d-b5b9-447d-b6b5-2b0c9f386400","year":2018},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.335764Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:e373161595221a163bef5455351f12bb27c9304daa79db866ee031d79ac6ced3","observation_id":"67124f2c-86eb-4446-a29d-782afd187ff6","resolution":{"observed_at":"2026-08-16T01:03:12.948841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.928441Z","title":"Achtermann; Indrajit Bhattacharya; Kevin W","venue":null,"work_id":"62c4466d-ab10-4cd1-bcef-b87f2c2155b4","year":2010},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.341483Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:acf90ce2fef4632e2e72792b87f01821a5aaa35b6e1afa34480e40c3084cde09","observation_id":"83500dfc-e419-49e2-ab6b-ff9c2b85859e","resolution":{"observed_at":"2026-08-16T01:03:12.933133Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.912747Z","title":"Supervised Clustering Loss for Clustering-Friendly Sentence Embeddings: Minimally Supervised Hierarchical Domain Intent Learning for CRS 15 an Application to Intent Clustering","venue":null,"work_id":"fab3447a-c8dd-4472-9490-7eb8b0b1e52d","year":2023},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.346910Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:a2baeb5e9a1af56bb243aa420fa0fb34e7f3eab79c3b44f95d3ba70faf8fb31f","observation_id":"5ad5ffaf-bac8-4ad4-b9e5-61b339aee095","resolution":{"observed_at":"2026-08-16T01:03:12.917998Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.897161Z","title":"Deep Embedded Clustering with Data Augmentation","venue":null,"work_id":"aa5ddcaf-6902-4c69-a24c-3940ff7cb5d9","year":2018},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.352570Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:f301638315382d7415927d2e68998f97c37ed548624f1e594878427a2efb1667","observation_id":"9bf2ab22-6bce-462b-9ad0-21c29c7eb91d","resolution":{"observed_at":"2026-08-16T01:03:12.902529Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06335","last_updated":"2016-05-24T22:27:35Z","snapshot_observed_at":"2026-08-14T22:22:10.022214Z","submitted_at":"2015-11-19T20:06:14Z","title":"Unsupervised Deep Embedding for Clustering Analysis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06335","snapshot_observed_at":"2026-08-16T01:03:12.357325Z","title":"Girshick, and Ali Farhadi","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.357325Z"},"links":{"cited_paper":"/paper/1511.06335","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:d314d9dc1aa60ce2811f4f4012e86e6a4ba660fc06f35588473da897f45c4f5d","observation_id":"01950dbe-277c-43eb-9ac5-d7c1a01a0286","resolution":{"observed_at":"2026-08-16T01:03:12.357325Z","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":"2026-08-16T01:03:12.881560Z","title":"An Unsupervised Neural Attention Model for Aspect Extraction","venue":null,"work_id":"9b9b3088-de93-449c-9cd4-e64fddf7abcc","year":2017},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.362584Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:d5c2bffe1c6784359326a93f906f81eb35a47888d0914ebc8e35b33c724e1ffd","observation_id":"23d4427c-ac7b-4a10-8e47-5db9b07f681c","resolution":{"observed_at":"2026-08-16T01:03:12.886450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1609.01454","last_updated":"2016-09-06T09:29:12Z","snapshot_observed_at":"2026-08-19T13:10:00.771785Z","submitted_at":"2016-09-06T09:29:12Z","title":"Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1609.01454","snapshot_observed_at":"2026-08-16T01:03:12.367495Z","title":null,"venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.367495Z"},"links":{"cited_paper":"/paper/1609.01454","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:c5dbc1c9c3176fc906288d1cc2a6d5ade0ae0d1a534ab25c2f55c6ee68d11522","observation_id":"13c9b66d-023a-4d4b-91fc-50eb4f53e931","resolution":{"observed_at":"2026-08-16T01:03:12.367495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1902.10909","last_updated":"2019-02-28T05:54:16Z","snapshot_observed_at":"2026-08-15T22:43:38.217495Z","submitted_at":"2019-02-28T05:54:16Z","title":"BERT for Joint Intent Classification and Slot Filling","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.10909","snapshot_observed_at":"2026-08-16T01:03:12.372942Z","title":"BERT for Joint Intent Classification and Slot Filling","venue":null,"work_id":null,"year":1902},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.372942Z"},"links":{"cited_paper":"/paper/1902.10909","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:4dfb0bba39bcea037072cfbfd6c04034c7903987733cdf289fa813d23ddae174","observation_id":"88bb2728-3b09-4a28-b28b-fe3e20fee4a2","resolution":{"observed_at":"2026-08-16T01:03:12.372942Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1911.08891","last_updated":"2019-11-20T13:26:43Z","snapshot_observed_at":"2026-07-06T08:38:27.678553Z","submitted_at":"2019-11-20T13:26:43Z","title":"Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement","version":1},"cited_work":{"arxiv_id":"1911.08891","doi":null,"metadata_source":"pith","pith_arxiv_id":"1911.08891","snapshot_observed_at":"2026-08-16T01:03:12.640358Z","title":"Discovering New Intents via Constrained Deep Adaptive Clustering with Cluster Refinement","venue":"cs.CL","work_id":"decf8032-cda2-4637-8b8c-37919c480be7","year":2019},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.378323Z"},"links":{"cited_paper":"/paper/1911.08891","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:689de58a569a2269dee216f47c93a382bb22e74287c0712a2a7c6ec090d51b8f","observation_id":"b2f857c0-ca96-4e76-bc06-aed84d6e70e4","resolution":{"observed_at":"2026-08-16T01:03:12.646487Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.11014","last_updated":"2021-01-18T13:45:27Z","snapshot_observed_at":"2026-08-05T07:38:41.221799Z","submitted_at":"2020-05-22T05:29:13Z","title":"Intent Mining from past conversations for conversational agent","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2005.11014","snapshot_observed_at":"2026-08-16T01:03:12.383422Z","title":"Intent Mining from past conversations for Conversational Agent.CoRR, abs/2005.11014, 2020","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.383422Z"},"links":{"cited_paper":"/paper/2005.11014","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:e2f0a08ee58a43fcf2bae8a4cf4cdd01d72d8ce13a308cb56d8309d7c042a381","observation_id":"1846b14f-0e0a-4b5a-a3ff-14852712f225","resolution":{"observed_at":"2026-08-16T01:03:12.383422Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2012.15504","last_updated":"2020-12-31T08:44:25Z","snapshot_observed_at":"2026-08-16T18:55:02.233788Z","submitted_at":"2020-12-31T08:44:25Z","title":"Continual Learning in Task-Oriented Dialogue Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.15504","snapshot_observed_at":"2026-08-16T01:03:12.387724Z","title":"Crook, Bing Liu, Zhou Yu, Eunjoon Cho, and Zhiguang Wang","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.387724Z"},"links":{"cited_paper":"/paper/2012.15504","citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:5be592f746449a190b83c49e05bc929bce902a88a83f2ff3ba9eaf314c401edf","observation_id":"732f3cd1-11ac-4f43-a1ff-3604f1da6fa3","resolution":{"observed_at":"2026-08-16T01:03:12.387724Z","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":"2026-08-16T01:03:12.865275Z","title":"Incremental Domain Adaptation for Neural Machine Translation in Low-Resource Settings","venue":null,"work_id":"f6d347ff-1306-48bc-896f-33f294f9bd25","year":2019},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.392994Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:eb632e868aac9d6cbee0f300b561585599d344fae90a870f54f0c2e62cf9ce65","observation_id":"2ae4eff4-ce3c-4238-a8d0-00bc03f5f2fb","resolution":{"observed_at":"2026-08-16T01:03:12.870677Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.848497Z","title":"Silhouettes: A graphical aid to the interpretation and validation of cluster analysis,","venue":null,"work_id":"68c3e009-dd41-4378-be0c-21679cd686f6","year":1987},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.397212Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:091b31b5393e2d095a61f57ea5fa5dfc6edbdc492526d603a9ac1ecb7330dbbd","observation_id":"217024d7-2ec1-4d2f-ac3b-48ec151a88ff","resolution":{"observed_at":"2026-08-16T01:03:12.853596Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.827186Z","title":"A dendrite method for cluster analysis,","venue":null,"work_id":"bd97592d-b0f5-47c6-9be9-c2dd8bfc0313","year":1974},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.401542Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:7156b76234345a4b50996276fa8a029644897899e4aa83799b8ad71cc35ae7c9","observation_id":"d303b1ef-9b46-41df-a71d-34a76b8f97f4","resolution":{"observed_at":"2026-08-16T01:03:12.836097Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.810532Z","title":"A cluster separation measure,","venue":null,"work_id":"8a637436-0f49-4a0a-ba64-792224bd7d1b","year":1979},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.405643Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:1ae28046755e19507f8c5dd418458f3d26752ba4fdd71d3b6147a9d0bbac1551","observation_id":"31ba72f2-1038-49a9-a27d-640957ac465b","resolution":{"observed_at":"2026-08-16T01:03:12.815379Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.794621Z","title":"Cluster ensembles—a knowledge reuse framework for combining multiple partitions,","venue":null,"work_id":"97047d01-3b15-4e6d-ad1f-898a4679ab20","year":2002},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.409949Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:29a8990e748ada712cb84625932062bea900cdb886ebbe91286d708111331ad9","observation_id":"590f86e3-9bae-40ac-9c4e-11dc8e2de067","resolution":{"observed_at":"2026-08-16T01:03:12.799270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.778395Z","title":"Comparing partitions,","venue":null,"work_id":"7f2efcee-8728-41f2-a18c-511f6f7f882d","year":1985},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.414933Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:3603056d0dfe9095cd239cde14064444d50715c61377255034d489146ec998e2","observation_id":"07bf12fc-7d47-4dc5-80c4-d7ca31f2430c","resolution":{"observed_at":"2026-08-16T01:03:12.783220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11229-020-02696-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-19T11:03:45.297681Z","title":"Algorithmic bias: on the implicit biases of social technology,","venue":"Synthese","work_id":"74fbe4bc-44df-4733-b4f6-fe96cc98e15b","year":2021},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.420389Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:a2171c042ee420a84ad442cc83faf9fe0aae695b238ab263d46ee44750b85500","observation_id":"c6a239c2-8770-46c1-ab21-7114b30cea68","resolution":{"observed_at":"2026-08-16T01:03:12.470407Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+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":"2026-08-16T01:03:12.425547Z","title":"Dial-In LLM: Human-Aligned LLM-in-the-loop Intent Clustering for Customer Service Dialogues,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.425547Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:1bbe8e8689254b87c61c62d7e49ec2205357cd022b3a509869a5c66a0004b58d","observation_id":"d7726314-f1a7-429d-a7b5-6c5c81648433","resolution":{"observed_at":"2026-08-16T01:03:12.425547Z","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":"2026-08-16T01:03:12.761002Z","title":"ClusterPrompt: Cluster Semantic Enhanced Prompt Learn- ing for New Intent Discovery,","venue":null,"work_id":"6a8c95d0-8b6b-4ff6-adcb-f05f0560464f","year":2023},"citing_paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T01:03:12.430383Z"},"links":{"citing_paper":"/paper/2505.02209"},"observation_digest":"sha256:141046de6f1d30aed8799f6b426c95da4ae42f6b015e451b3ded6239bf85c036","observation_id":"c6c60c2b-e39d-4de8-bce9-dd3a856856da","resolution":{"observed_at":"2026-08-16T01:03:12.767028Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2505.02209","last_updated":"2025-05-04T18:12:54Z","latest_version":1,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-20T04:28:26.199152Z","submitted_at":"2025-05-04T18:12:54Z","title":"Minimally Supervised Hierarchical Domain Intent Learning for CRS"},"reference_resolution":{"displayed":23,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":4,"verified_fuzzy":13},"total_outbound_references":23},"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":"2026-08-20T06:33:59.587034+00:00","source":"crossref"},{"observed_at":"2026-08-20T06:33:54.927442+00:00","source":"retraction_watch"}],"thesis":"As of 20 August 2026, this Paper Citation Record lists 23 of 23 outbound references and 0 inbound Pith citation observations for arXiv:2505.02209."}