{"as_of":"2026-08-21T12:01:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:00fb4a82e2586721700abcc628008fde0e51e5cf214db087cb3b8ad1aeb8148a","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":8,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":8,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+00:00","state":"measured"},{"denominator":8,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":8,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-15T23:30:58.388524Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-05-25T18:41:08.236970Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":"1702.07983","doi":null,"metadata_source":"pith","pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","venue":"cs.AI","work_id":"c9ec1966-b7dd-40c3-ac14-81d217a41ffa","year":2017},"citing_paper":{"arxiv_id":"1906.09379","last_updated":"2019-06-22T03:24:32Z","snapshot_observed_at":"2026-07-06T08:02:05.321699Z","submitted_at":"2019-06-22T03:24:32Z","title":"Evaluating Computational Language Models with Scaling Properties of Natural Language","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-25T18:40:15.883063Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/1906.09379"},"observation_digest":"sha256:b4c9d6712d03edba554544fa476ae61295130f6be11185b5343110bad0a100c7","observation_id":"9293f7d9-90fc-4436-9558-d8a053a1ee82","resolution":{"observed_at":"2026-05-25T18:41:08.240350Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":"1702.07983","doi":null,"metadata_source":"pith","pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","venue":"cs.AI","work_id":"c9ec1966-b7dd-40c3-ac14-81d217a41ffa","year":2017},"citing_paper":{"arxiv_id":"1907.05671","last_updated":"2019-07-12T10:51:48Z","snapshot_observed_at":"2026-08-19T03:39:57.149148Z","submitted_at":"2019-07-12T10:51:48Z","title":"Justifying Diagnosis Decisions by Deep Neural Networks","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-24T22:30:58.845280Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/1907.05671"},"observation_digest":"sha256:99acd1612352048ebcb32d9ba7ab3aa3466f8068e474431d5d36eb1e33697804","observation_id":"0d4bcd34-2285-45a5-8e98-3db29a751047","resolution":{"observed_at":"2026-05-24T22:35:01.975258Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-08-14T12:28:33.864533Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07195","last_updated":"2019-08-20T07:25:14Z","snapshot_observed_at":"2026-08-19T23:33:53.951436Z","submitted_at":"2019-08-20T07:25:14Z","title":"ARAML: A Stable Adversarial Training Framework for Text Generation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-14T12:28:33.864533Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/1908.07195"},"observation_digest":"sha256:8a37ec90a4f840c8578f71cb58c074bc0d7c26c66941fe7afb4ff4a5ee901742","observation_id":"471ba842-4157-4eef-a779-7c022f2a79ed","resolution":{"observed_at":"2026-08-14T12:28:33.864533Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-08-14T11:28:08.523512Z","title":null,"venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.09127","last_updated":"2020-10-15T10:25:10Z","snapshot_observed_at":"2026-08-21T11:58:54.880714Z","submitted_at":"2019-08-24T11:39:50Z","title":"DGSAN: Discrete Generative Self-Adversarial Network","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T11:28:08.523512Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/1908.09127"},"observation_digest":"sha256:2e9560c8e3652ef3a9de299ae28fee5f670d3e9f6d1fd0fc7e8f7e7ba13915b7","observation_id":"ec62fa43-2125-4730-8927-f4772a97786e","resolution":{"observed_at":"2026-08-14T11:28:08.523512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-08-14T05:36:43.322474Z","title":"D.; Li, W.; Song, Y.; and Bengio, Y","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1909.00925","last_updated":"2019-09-04T18:23:54Z","snapshot_observed_at":"2026-08-19T09:07:21.753401Z","submitted_at":"2019-09-03T02:45:28Z","title":"Adversarial Bootstrapping for Dialogue Model Training","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-14T05:36:43.322474Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/1909.00925"},"observation_digest":"sha256:ea04873e8a3e0d06fefa0bfb63e9843184c8805e8f2b7fb8ba0d0f791c633c0d","observation_id":"5c605c9c-c258-43df-af3d-4154099a784f","resolution":{"observed_at":"2026-08-14T05:36:43.322474Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":"1702.07983","doi":null,"metadata_source":"pith","pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","venue":"cs.AI","work_id":"c9ec1966-b7dd-40c3-ac14-81d217a41ffa","year":2017},"citing_paper":{"arxiv_id":"2104.05565","last_updated":"2022-03-15T21:02:38Z","snapshot_observed_at":"2026-08-14T01:07:54.466395Z","submitted_at":"2021-04-12T15:33:11Z","title":"Survey on reinforcement learning for language processing","version":3},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-24T12:54:27.155842Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/2104.05565"},"observation_digest":"sha256:080d4b5bc66682414d42398525aaaa578e3069034b577fc6914f2c9a4983b02b","observation_id":"0bf7431b-56f6-4fbd-8926-382a0d35080f","resolution":{"observed_at":"2026-05-24T12:54:29.768964Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-08-15T23:30:58.388524Z","title":"Devon Hjelm, Wenjie Li, Yangqiu Song, and Yoshua Bengio","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2505.04507","last_updated":"2025-05-07T15:27:59Z","snapshot_observed_at":"2026-08-19T11:57:22.627459Z","submitted_at":"2025-05-07T15:27:59Z","title":"Detecting Spelling and Grammatical Anomalies in Russian Poetry Texts","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-15T23:30:58.388524Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/2505.04507"},"observation_digest":"sha256:b3f118ec9ab1be221ed2044f997042ba43435f174fcd7f61d66b38c530e08cdd","observation_id":"4bf0f934-ab8b-46f0-98cf-9c290f05a9cb","resolution":{"observed_at":"2026-08-15T23:30:58.388524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.07983","snapshot_observed_at":"2026-08-06T21:24:19.712510Z","title":"Maximum-likelihood augmented discrete generative adversarial networks.ArXiv preprint, abs/1702.07983, 2017","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2507.00425","last_updated":"2025-07-01T04:51:25Z","snapshot_observed_at":"2026-08-21T09:09:06.893160Z","submitted_at":"2025-07-01T04:51:25Z","title":"Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T21:24:19.712510Z"},"links":{"cited_paper":"/paper/1702.07983","citing_paper":"/paper/2507.00425"},"observation_digest":"sha256:1a169be05d7f6dae05619a4063b705feb76e5ebdc48abbdd75c336c3cceacc2a","observation_id":"6e5a3bbf-71ad-4ca9-88f3-ab5493f6af70","resolution":{"observed_at":"2026-08-06T21:24:19.712510Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1702.07983/citation-record","integrity":"/paper/1702.07983/integrity","json":"/paper/1702.07983/citation-record.json","paper":"/paper/1702.07983"},"outbound":[],"paper":{"arxiv_id":"1702.07983","last_updated":"2017-02-26T03:19:13Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-17T17:46:07.594046Z","submitted_at":"2017-02-26T03:19:13Z","title":"Maximum-Likelihood Augmented Discrete Generative Adversarial Networks"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:1702.07983."}