{"as_of":"2026-08-16T03:22:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:af3a84f9c887e2469e3b5e35a4d655a201ef2d7134d9263e515d15d0cbb6f246","coverage":[{"denominator":37,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":37,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T13:21:40.008202Z","state":"measured"},{"denominator":37,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":37,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-15T06:32:42.880941+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/1908.05324/citation-record","integrity":"/paper/1908.05324/integrity","json":"/paper/1908.05324/citation-record.json","paper":"/paper/1908.05324"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T13:21:40.566938Z","title":"Augmented cyclegan: Learning many-to-many mappings from unpaired data","venue":null,"work_id":"86939cb0-8c5e-403f-9567-2ceceeadf066","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.864279Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:1549b07f20f8c08b30e90072ba9eea82b9773663e63a1257b42fe69c51a09ade","observation_id":"373de361-285c-4e72-836d-c5354cb8d309","resolution":{"observed_at":"2026-08-14T13:21:40.570787Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.555164Z","title":"Adversarial learning of semantic relevance in text to image synthesis","venue":null,"work_id":"b3d78931-f496-4123-8575-d705bdbb769e","year":2019},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.868855Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:eb029c3a32b029e663747cd52a27de8b94dcc36d61453a5dbb3a8097e2acd26c","observation_id":"07ec852a-4490-4ba0-a4aa-c048869f6e91","resolution":{"observed_at":"2026-08-14T13:21:40.559807Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.542125Z","title":"Infogan: Interpretable rep- resentation learning by information maximizing generative adversarial nets","venue":null,"work_id":"514e4e11-94fe-4ecf-86ee-d9db5900fc14","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.872598Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:a7121cc198ac9bd96ff5bdb56a3ef5141c7e4f80c5f93a33302ef75e9accc70f","observation_id":"c71757a0-e16a-4408-b36c-5c85f6fd44fe","resolution":{"observed_at":"2026-08-14T13:21:40.547106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.530634Z","title":"Independent component analysis, a new con- cept? Signal processing, 36(3):287–314, 1994","venue":null,"work_id":"febb0442-7186-4652-bf5c-4c0a9ae70556","year":1994},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.876342Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:d71b2208420b87da39ee3aa14bb827dddb323ef05c7274e2a177e869bb85652b","observation_id":"70984c87-4f15-4cea-83e2-52130d52fecb","resolution":{"observed_at":"2026-08-14T13:21:40.534843Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1703.06412","last_updated":"2017-03-26T11:29:21Z","snapshot_observed_at":"2026-08-14T21:11:09.664503Z","submitted_at":"2017-03-19T10:07:58Z","title":"TAC-GAN - Text Conditioned Auxiliary Classifier Generative Adversarial Network","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1703.06412","snapshot_observed_at":"2026-08-14T13:21:39.880250Z","title":"Tac-gan-text conditioned auxiliary classifier generative ad- versarial network","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.880250Z"},"links":{"cited_paper":"/paper/1703.06412","citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:4d65ee51b1be5264d3e86e607264146f442d391dedc783c28cefb51a3a383733","observation_id":"5b91c204-1aa7-4bb1-a4bf-541949be8c60","resolution":{"observed_at":"2026-08-14T13:21:39.880250Z","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":"2026-08-14T13:21:40.517752Z","title":"Ad- versarial feature learning","venue":null,"work_id":"13ba5b9f-9b83-4c40-a8c9-bdb9dc702f3f","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.885354Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:a01ad35ff36b167594cfb03e8fec56fd184f17755bacab5dcb315d10291e8535","observation_id":"e3032e35-9622-4288-becb-e7f5ad6b8baf","resolution":{"observed_at":"2026-08-14T13:21:40.522403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.507037Z","title":"Adversarially learned inference","venue":null,"work_id":"aa6e4beb-be5b-44b5-964b-ffe7b86da402","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.889249Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:bb2a27855a1964a9735c24e1c86321f1076b72a9d252d4cc9250b9f4ddb2b5c9","observation_id":"52f765b0-51c1-4dd1-a445-fe51a36d6ef6","resolution":{"observed_at":"2026-08-14T13:21:40.510524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.496376Z","title":"Image-to-image translation for cross-domain disentan- glement","venue":null,"work_id":"640a3404-c53c-477c-8105-1d55e6069eae","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.893329Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:b3a2bb4347f5f01e912f6e1a4cac8d2178f29cd14e07dbf7cee8dfc8d10cfd42","observation_id":"3db4c50b-baf6-4192-8c44-a24f0af4f91e","resolution":{"observed_at":"2026-08-14T13:21:40.499891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.485515Z","title":"Generative adversarial nets","venue":null,"work_id":"f126594f-5e5f-4ccd-8029-811853bc9be4","year":2014},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.897227Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:a1f38c3bdcaaf2c96946edf9142696f9060c44bf8f00feed61049ef2119a7f3c","observation_id":"50676f40-866c-4b24-8be7-4a10663a47cb","resolution":{"observed_at":"2026-08-14T13:21:40.489198Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.474360Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium","venue":null,"work_id":"1cf5f9ef-5554-46b5-9710-d238ac49b8f0","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.901637Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:ceab4952aff1b142628cb8656959a100d8caa3beea1b370c0d16ca5957e6a5af","observation_id":"3779b16a-88ce-457c-ae5e-1ff99d3b52e4","resolution":{"observed_at":"2026-08-14T13:21:40.478284Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:39.906454Z","title":"beta-vae: Learning basic visual con- cepts with a constrained variational framework","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.906454Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:bf8a747f3721362de3ec8f5c002b80feb8e502e505846ba3ce454c330066b11f","observation_id":"1dfa73c1-a895-42a2-bccf-ffa2c1ae6bc6","resolution":{"observed_at":"2026-08-14T13:21:39.906454Z","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":"2026-08-14T13:21:40.454073Z","title":"Inferring semantic layout for hierarchical text- to-image synthesis","venue":null,"work_id":"7205c950-2a59-437a-a461-a0376326d055","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.910424Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:9e9e059e40b71159ce4d989aa67adc70d581fe2a4265918e9b7f2cebad27ed30","observation_id":"89268fde-94e6-470f-8fdd-1a9d25c83a1f","resolution":{"observed_at":"2026-08-14T13:21:40.459243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.441813Z","title":"Variational autoencoders and nonlinear ica: A unifying framework","venue":null,"work_id":"c1ef94c2-2aeb-4e09-a7c3-4b13b7d6f711","year":2019},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.914454Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:e9d09ff151ab51c4863785be3cdfd88ea371ed807452bfaa14c66f990fa6b683","observation_id":"14796bbf-537a-49b7-98f8-ce9d8fe9ec46","resolution":{"observed_at":"2026-08-14T13:21:40.445819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.429952Z","title":"Learning to discover cross-domain relations with generative adversarial networks","venue":null,"work_id":"36b8d31d-dbbe-4560-8920-b63ea891ea6b","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.918061Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:57f3c1e3e6ec659af7603234c3a6a1edecadc031baf6d9f0bcffd913131081d0","observation_id":"642db95d-7056-4b69-ac60-673421958777","resolution":{"observed_at":"2026-08-14T13:21:40.433976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.419479Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":"2cc36fd5-8635-436e-b755-f84c68bb4f70","year":2015},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.921847Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:9f8500875a7594d8d6e3146fc1de5181ddbb7df229880bd167b7d2c8dcd29c0d","observation_id":"4a977ff7-c111-4132-a568-97357c973e47","resolution":{"observed_at":"2026-08-14T13:21:40.423152Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.408461Z","title":"Auto-encoding varia- tional bayes","venue":null,"work_id":"e57d26a6-10a8-4e42-84b8-a89b7f655b8b","year":2014},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.925978Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:8165dcbcf3394c028f7f43e60c30767c00d7e2271e861dd908a12b21c8a28cb8","observation_id":"4f007d90-cf13-4a1e-9ec8-578d1e37486a","resolution":{"observed_at":"2026-08-14T13:21:40.412185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.396790Z","title":"Autoencoding beyond pixels using a learned similarity metric","venue":null,"work_id":"0048b9f4-c619-462d-8883-7857448c4507","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.929546Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:184882107057e56b11a9c7f2c81e92ca2eab19b6917f52eea73d6b13f614b7a5","observation_id":"de06a6bc-37ef-44d6-867d-3f960eb72e93","resolution":{"observed_at":"2026-08-14T13:21:40.401089Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:39.933155Z","title":"Diverse image-to-image translation via disentangled representations","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.933155Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:76fbfec0935edb44210b8ac2ef5eb91946dadddd96e0e2491edf4244dc0d5e30","observation_id":"bacac704-6c4b-49d3-b392-01f78eaebb6b","resolution":{"observed_at":"2026-08-14T13:21:39.933155Z","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":"2026-08-14T13:21:40.378400Z","title":"Alice: To- wards understanding adversarial learning for joint distribu- tion matching","venue":null,"work_id":"f29445c9-bcef-4b0a-a075-6a5f5becbbd4","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.937144Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:40f1af362e29ef535c182e2991268981ba0e10286267718ca8287159462993fb","observation_id":"ea1a653b-1121-4d55-b68e-56b478568639","resolution":{"observed_at":"2026-08-14T13:21:40.382246Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.366607Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":"ede42653-c094-4153-ac3a-8779bafe85fe","year":2014},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.941358Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:5cb3e3b571feb3d21b75e667e31680762c0a6c48d0351aaa0e0d8dc1e70a2139","observation_id":"d3fcb613-e83e-45a7-bfab-7132a26fb274","resolution":{"observed_at":"2026-08-14T13:21:40.370796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.356103Z","title":"Are gans created equal? a large-scale study","venue":null,"work_id":"cefef799-f512-474f-9c5e-75dbdfd191a1","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.945083Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:e6a2175d60ee278488e87b3238dabefa3853a691f7ece5f0ac4fbe57bc2f437a","observation_id":"bdb0e136-c3a2-4869-9f70-67731634281f","resolution":{"observed_at":"2026-08-14T13:21:40.360027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1411.1784","last_updated":"2014-11-06T22:33:22Z","snapshot_observed_at":"2026-08-12T18:51:00.108451Z","submitted_at":"2014-11-06T22:33:22Z","title":"Conditional Generative Adversarial Nets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1411.1784","snapshot_observed_at":"2026-08-14T13:21:39.948663Z","title":"Conditional generative adversarial nets","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.948663Z"},"links":{"cited_paper":"/paper/1411.1784","citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:54deff64fab823ad69d4d3790afd8fdb01093afbad764d111b03e8d9c76d243d","observation_id":"bcc3bd09-8845-42b7-96de-6af774590ef5","resolution":{"observed_at":"2026-08-14T13:21:39.948663Z","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":"2026-08-14T13:21:40.345581Z","title":"Automated flower classification over a large number of classes","venue":null,"work_id":"b4888f36-8f6e-49b7-a140-412d5b4d4f0a","year":2008},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.952585Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:1ec7158e151d942e6485f5351f94c8bea3591f9c2dadacfc3616b28b3990c1a8","observation_id":"c02b2be3-bd91-4c3c-b227-72594120775c","resolution":{"observed_at":"2026-08-14T13:21:40.349255Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.334337Z","title":"Mirrorgan: Learning text-to-image generation by redescrip- tion","venue":null,"work_id":"1c9a4aac-ac74-49e4-b9c7-5bb61e94e19b","year":2019},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.956222Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:fc563044060d5a4b0df60630264f1b76729de18f76ac504e7b4c04ceaf8d4685","observation_id":"86ccf760-ad59-4871-a6af-11f10867b821","resolution":{"observed_at":"2026-08-14T13:21:40.338312Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.323147Z","title":"Learning deep representations of fine-grained visual descrip- tions","venue":null,"work_id":"f73a84a4-f32d-4250-8260-250f4671862d","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.959812Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:e61b0d33d66c889a5df0dfb3711148406cf7d5e1434c5777f8e6a8f4deb95036","observation_id":"55652fd5-32ce-4cfc-aa02-83afcbc0643f","resolution":{"observed_at":"2026-08-14T13:21:40.327560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.313047Z","title":"Generative ad- versarial text to image synthesis","venue":null,"work_id":"16854bb2-5fd9-412d-a630-ed38661e3b99","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.963231Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:3ff5598deeb634a7e86d4766a4096e0b47698e6e91903277dd0c6157b82f04d3","observation_id":"52a14620-308d-40a8-aed7-bb866b6df8c3","resolution":{"observed_at":"2026-08-14T13:21:40.316648Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.302104Z","title":"Learning what and where to draw","venue":null,"work_id":"ec7decbc-22d1-41dd-9d3d-6e3f3b519ddd","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.967387Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:832aabde9120e47e08b3420ef852590fdf9c6b3067340eb40d8e0ceab0ae5a0f","observation_id":"54779dc8-dd28-44a8-ad48-3125b55d1b02","resolution":{"observed_at":"2026-08-14T13:21:40.305844Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.288782Z","title":"Improved techniques for training gans","venue":null,"work_id":"69239381-82fd-4984-a955-6c24d04a41f6","year":2016},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.971629Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:37f465631a5aee0703d065c98fa91d27ffa18fa9f9a3668eca3ab25fd0aabee0","observation_id":"e30358bf-c247-4a51-96e5-7a7b0f3f34f4","resolution":{"observed_at":"2026-08-14T13:21:40.294611Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.158028Z","title":"Caltech-ucsd birds 200","venue":null,"work_id":"d5db6e0a-f57c-4c56-9125-4a10a475bc31","year":2010},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.975062Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:5ce549fc52fa50524b2a4cc4e1d20b5c6060a5b33fd729b749a1cc2f919437cf","observation_id":"cf0f707e-4ff1-436f-a111-b466eec44865","resolution":{"observed_at":"2026-08-14T13:21:40.162234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.146577Z","title":"Attngan: Fine- grained text to image generation with attentional generative adversarial networks","venue":null,"work_id":"dc44e203-c17c-4f1b-b83f-2accd2fee4c3","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.978948Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:435d1af04c230f7983cc7bb21769fbf1d2f5a2d945a1e087de3afad2a6a64114","observation_id":"227b544f-a99f-483d-a133-d25972278ec8","resolution":{"observed_at":"2026-08-14T13:21:40.150530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.133932Z","title":"Dualgan: Unsupervised dual learning for image-to-image translation","venue":null,"work_id":"ad7b0701-009a-4ee7-8ce7-b5dd7d6d5b93","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.982460Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:cf91b20c8e429859dbcdf98e5a4fde414b184736fbd2803e177defcf4d3ef7ac","observation_id":"e4bd4986-81a2-4d17-bbea-574cbdc47ba9","resolution":{"observed_at":"2026-08-14T13:21:40.139172Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.122314Z","title":"Stackgan: Text to photo-realistic image synthesis with stacked genera- tive adversarial networks","venue":null,"work_id":"40e04128-d69a-4a80-96ee-386c1a938448","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.986252Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:c69aacefdb0f4953385eec849c2db8a8138986b5533f2ad6643b35011a6f4f85","observation_id":"5ce9c454-7eaf-42be-9951-ed262dc4aba0","resolution":{"observed_at":"2026-08-14T13:21:40.126226Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10916","last_updated":"2018-06-28T00:49:19Z","snapshot_observed_at":"2026-08-14T20:22:05.208461Z","submitted_at":"2017-10-19T18:45:59Z","title":"StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10916","snapshot_observed_at":"2026-08-14T13:21:39.990196Z","title":"Stack- gan++: Realistic image synthesis with stacked generative adversarial networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.990196Z"},"links":{"cited_paper":"/paper/1710.10916","citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:a4c4b97820ab25317a5a2f6d031b03a30d10c96bc64316b05cc196a84af87777","observation_id":"008b5aac-c359-4a22-b62e-997a75689719","resolution":{"observed_at":"2026-08-14T13:21:39.990196Z","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":"2026-08-14T13:21:40.110406Z","title":"Separating style and content for generalized style transfer","venue":null,"work_id":"8a5f9512-cf54-44b5-b2fb-fc2bd7147714","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.994606Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:cd1b6a32928966038ad6e7de4800f8152ae28729c40fda73b07c23185633d16f","observation_id":"867a00ef-2893-4d6a-9de1-b0485df1819c","resolution":{"observed_at":"2026-08-14T13:21:40.114361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.097943Z","title":"Photographic text-to-image synthesis with a hierarchically-nested adver- sarial network","venue":null,"work_id":"739ec709-1cec-4e97-b43b-68006c55fc8e","year":2018},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:39.998531Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:f676e40219f48ab9a6d61244299c6839d30faa65cda863147305bc6de517f7f9","observation_id":"e9ab9756-eb11-4801-9fd6-533bcfe7638c","resolution":{"observed_at":"2026-08-14T13:21:40.102640Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.085311Z","title":"Unpaired image-to-image translation using cycle- consistent adversarial networkss","venue":null,"work_id":"fa46b4f6-6151-4c7c-871d-d301e4ab76a5","year":2017},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:40.003138Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:b9cfd5bb8058ec6fa77aa4d94adcd71cd02f4a7a8f5afe1f93e1e5e50cb1a537","observation_id":"5539b293-7c20-456d-8e9b-c6cb8bd234e3","resolution":{"observed_at":"2026-08-14T13:21:40.090222Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+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":"2026-08-14T13:21:40.070350Z","title":null,"venue":null,"work_id":"dad2d29c-23e9-4238-8830-bf709603d763","year":null},"citing_paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T13:21:40.008202Z"},"links":{"citing_paper":"/paper/1908.05324"},"observation_digest":"sha256:85a93a332f39b396a54526c597ead51af025b2eb028ad47f6c32e95e6946b8af","observation_id":"b8278a79-769a-4264-90ae-720f8782bd44","resolution":{"observed_at":"2026-08-14T13:21:40.076274Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.05324","last_updated":"2019-08-14T19:35:02Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-16T01:33:16.928713Z","submitted_at":"2019-08-14T19:35:02Z","title":"Dual Adversarial Inference for Text-to-Image Synthesis"},"reference_resolution":{"displayed":37,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":6,"verified_exact":0,"verified_fuzzy":31},"total_outbound_references":37},"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":"2026-08-15T06:32:42.880941+00:00","source":"crossref"},{"observed_at":"2026-08-15T06:32:39.529945+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:1908.05324."}