{"as_of":"2026-08-18T21:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:a1e682bad97e2ed566db7e5a8bd88b728acd63d916588e18b698dc74196dae13","coverage":[{"denominator":22,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-25T17:13:41.750884Z","state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+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/1906.10244/citation-record","integrity":"/paper/1906.10244/integrity","json":"/paper/1906.10244/citation-record.json","paper":"/paper/1906.10244"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Power to the people: The role of humans in interactive machine learning","venue":null,"work_id":"346a4c2e-3604-4e9a-884c-029f180ec284","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:46731eeffc034160d1efd92be732dbf79c1cb036c4cc1fdd262fad4268c95f7a","observation_id":"6f11c5b6-1cad-48fd-b5a5-c4fb09aa5cac","resolution":{"observed_at":"2026-05-25T17:16:05.410159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Do explanations make vqa models more predictable to a human? EMNLP","venue":null,"work_id":"0f1cc06f-996c-41eb-b685-e858aec79de4","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:e492f4e848ebc440e88a431ff5e15b27911bf4480b5c79c6ac37ada6c3b88b78","observation_id":"0d9d9123-0609-4cd3-b5de-cec2908f73ed","resolution":{"observed_at":"2026-05-25T17:16:05.413876Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Global fintech investment robust on back of strong vc funding:kpmg","venue":null,"work_id":"a3809c63-82ff-4ce0-831d-4dc0270c3a5e","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:db38c2d7be0386d8eb7bd5c9b7b9a16ba93dd3229c2b9151a93c02fc5a6832fa","observation_id":"f3074c7a-5793-44be-b70f-4e4225df90fc","resolution":{"observed_at":"2026-05-25T17:16:05.406284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"What does explainable ai really mean? a new conceptualization of perspectives","venue":null,"work_id":"203e1e0c-b710-4d1c-a68f-9a1f5563a73a","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:b7bee335223ac04fc725a530181186de6641405065b136f62fd19547f57831e8","observation_id":"806fa3e7-47f2-412f-aaa3-e63406368ec8","resolution":{"observed_at":"2026-05-25T17:16:05.386182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Towards a rigorous science of interpretable machine learning","venue":null,"work_id":"02f9481a-c764-472c-9b21-5792e7480d5c","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:6208abbcc0bf377030449493b6b713a2e971ae1e4283db660a061c58711aa7f2","observation_id":"901768db-029d-4472-b433-82b2a76b700c","resolution":{"observed_at":"2026-05-25T17:16:05.371193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Accountability of ai under the law: The role of explanation","venue":null,"work_id":"f3821adc-d493-4bb0-8007-a96afce11590","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:0000824053d5ccfd94745657360da092ab038c5db623205050cd8aaa760818ec","observation_id":"e74cbdab-ec1d-4d82-a323-8bd944dacfef","resolution":{"observed_at":"2026-05-25T17:16:05.378559Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Machine learning and fico scores: An evolution in ml innovations that helps both lenders and consumers","venue":null,"work_id":"94e8a5d4-68b9-492a-86e8-ace2e4280177","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:e1d5af67625c611c81340c496efa73b75f21c57185c5cc90810c284ddc6ab8e2","observation_id":"da50561e-83c2-45dc-a2fc-3b29fb526659","resolution":{"observed_at":"2026-05-25T17:16:05.433477Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"xai toolkit: Practical, explainable machine learning","venue":null,"work_id":"589fcfbe-d9c6-4b19-a68e-2e8a9398ad45","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:7fe66cd02f9e8725eaf444534aaa71a6605a18e77d52006ef7768d5d2839856b","observation_id":"0cc8df60-dec8-49ef-8ca9-422207222632","resolution":{"observed_at":"2026-05-25T17:16:05.390061Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Explainable artificial intelligence","venue":null,"work_id":"c011de59-2f9b-4873-92a4-88949dccff41","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:f476914ebe49f1a8e9dcdb516e3947a7ecd8a0a5bbef2d3f46b00f6f3a35880e","observation_id":"81148b43-f83c-4220-ad50-db7cd339c2c6","resolution":{"observed_at":"2026-05-25T17:16:05.417743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Deligan: Generative adversarial networks for diverse and limited data","venue":null,"work_id":"f74ed248-a774-4683-a4b6-e66379bda2ab","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:6a422d8466ec5df91fe84f740988315994e321b37896a6bbc68d9ec58515501d","observation_id":"bef6e9e5-642d-4092-86d5-7aae1ccf504b","resolution":{"observed_at":"2026-05-25T17:16:05.364116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"The promise and peril of human evaluation for model interpretability","venue":null,"work_id":"98ada4e0-6d10-403e-ae3c-b80cea94d3c7","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:81fb0b9b8e7bb31311f1df2ff986781ac4dba9a1987ee817ffe837d828a73362","observation_id":"21c8669d-0e69-4abf-839f-b018c75d24ae","resolution":{"observed_at":"2026-05-25T17:16:05.402007Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Learning overhypotheses with hierarchical bayesian models","venue":null,"work_id":"0a6ccded-bda4-45fb-a9b8-02c9715a2175","year":2007},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:c114920e4557556259a7b19964334bf32de515c70c0dfa3f57952de15554bc21","observation_id":"5e978c42-19cb-46b5-9f15-53c45dddec10","resolution":{"observed_at":"2026-05-25T17:16:05.398309Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1709.02023","last_updated":"2017-09-14T22:52:47Z","snapshot_observed_at":"2026-08-15T05:59:06.977382Z","submitted_at":"2017-09-06T22:53:12Z","title":"CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training","version":2},"cited_work":{"arxiv_id":"1709.02023","doi":null,"metadata_source":"pith","pith_arxiv_id":"1709.02023","snapshot_observed_at":"2026-07-11T02:47:49.090088Z","title":"CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training","venue":"cs.LG","work_id":"834366f6-626a-4255-9bd1-3b91dd11c9bc","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"cited_paper":"/paper/1709.02023","citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:5616b0d8a90597c789751420ea4986021e1b5e3bbd5c5b6455a1359bf974f11a","observation_id":"1768083c-ca61-4cc3-8303-1e6514d5f1ca","resolution":{"observed_at":"2026-05-25T17:16:04.586925Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"How explainability is driving the future of artificial intelligence","venue":null,"work_id":"f9765264-5785-42c9-9a9d-50d512c8d053","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:46e705caea0e7621d6f4ea091e58c78b6b56c9946dda104c6b7dff805e9a50d5","observation_id":"7ba0f2de-11b7-4f19-ac45-40bee8744530","resolution":{"observed_at":"2026-05-25T17:16:05.374987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"The mythos of model interpretability","venue":null,"work_id":"a89930eb-ea59-434e-8893-adfdefdfa756","year":2016},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:c1ed26fda440062d03160a9e4cb788245f5a36c52057cfbc39bba02cff4a7000","observation_id":"e956682b-4052-43c7-98e0-05304d560f40","resolution":{"observed_at":"2026-05-25T17:16:05.367563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Explainable ai: Beware of inmates running the asylum","venue":null,"work_id":"18420482-8e7d-4dcc-b76b-a17fcc75a896","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:cb61685976dd966f24880932139081a3cf9610d9dd28034a40ba39757e123f5e","observation_id":"17c9c32d-1771-4440-856c-c4f5180e58c4","resolution":{"observed_at":"2026-05-25T17:16:05.394161Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"How do humans understand explanations from machine learning systems:an evaluation of the human-interpretability of explanation","venue":null,"work_id":"edb01288-9368-4eb3-86f7-5df30a36d73a","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:99a110a5c92bf2d924f95c7363e403c17326c6e8812bc8148046fe6f5d6434e9","observation_id":"023c53f0-0d34-4c93-b475-ec1bdeda7c18","resolution":{"observed_at":"2026-05-25T17:16:05.425602Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"5923eeb2-bbc7-44c2-a8c5-d9605324d17c","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:2218b2722024499df7850a637021cf8027af663e692429b1076e2d19f9dcfe4b","observation_id":"66ce9076-edd6-4629-953d-2e842b4d98e6","resolution":{"observed_at":"2026-05-25T17:16:05.429323Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Explainable ai driving business value through greater understanding","venue":null,"work_id":"61807e55-e116-4bfc-a3dd-f391e65b3d7a","year":2018},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:6e48b20363168ea0f6015aa57ab3b87275211fa3170b4f544e2dc64137d11fd6","observation_id":"2b58c4b3-3c16-49fc-944b-85b06b659723","resolution":{"observed_at":"2026-05-25T17:16:05.382186Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Why should i trust you? explaining the predictions of any classifier","venue":null,"work_id":"c08b2ca5-0b1d-41a6-9a41-7fddde570659","year":2016},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:dfd796be968a0c0f7a2683d0bcfd8964838144a21734d142d13e9a7bbb7a2b6f","observation_id":"053430e0-fe3d-4005-847b-e85ceba31a01","resolution":{"observed_at":"2026-05-25T17:16:05.421592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-06-05T21:23:00.469572Z","title":"Selvaraju, A","venue":null,"work_id":"8207e757-b84b-44b3-80f0-7c2669a9d231","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:5f91e51a0d26170e6fbb5da5b7d94a4cba8e35e6a88971ca3f35e9bd8052628e","observation_id":"c83b65fe-8c2d-4e28-8481-21bce840a4d9","resolution":{"observed_at":"2026-05-25T17:16:05.437099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.04223","last_updated":"2018-06-29T00:07:16Z","snapshot_observed_at":"2026-08-14T20:54:16.171553Z","submitted_at":"2017-06-13T19:00:53Z","title":"Adversarially Regularized Autoencoders","version":3},"cited_work":{"arxiv_id":"1706.04223","doi":null,"metadata_source":"pith","pith_arxiv_id":"1706.04223","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Adversarially Regularized Autoencoders","venue":"cs.LG","work_id":"48770141-4574-4a0d-87f9-d053cb86681e","year":2017},"citing_paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-05-25T17:13:41.750884Z"},"links":{"cited_paper":"/paper/1706.04223","citing_paper":"/paper/1906.10244"},"observation_digest":"sha256:64017555d15f7b820fb3ed414ccbdae1af8c35dc3ab2ed0237727fe4166d5eae","observation_id":"c645aee4-521a-40b5-bb92-efa2cca98734","resolution":{"observed_at":"2026-05-25T17:16:04.591728Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1906.10244","last_updated":"2019-06-24T21:41:55Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-07-06T08:02:30.592084Z","submitted_at":"2019-06-24T21:41:55Z","title":"Generating User-friendly Explanations for Loan Denials using GANs"},"reference_resolution":{"displayed":22,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":2,"verified_fuzzy":19},"total_outbound_references":22},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 22 of 22 outbound references and 0 inbound Pith citation observations for arXiv:1906.10244."}