{"as_of":"2026-08-16T14:30:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c49588fd1ea61f1c307055b5ff42483f801ddc18e43fc89c0eca9c09254c215f","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-14T12:22:17.571336Z","state":"measured"},{"denominator":39,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":39,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-16T06:30:59.297886+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/1908.07500/citation-record","integrity":"/paper/1908.07500/integrity","json":"/paper/1908.07500/citation-record.json","paper":"/paper/1908.07500"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"1809.11096","last_updated":"2019-02-25T21:32:06Z","snapshot_observed_at":"2026-07-06T07:04:57.275371Z","submitted_at":"2018-09-28T15:38:49Z","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.11096","snapshot_observed_at":"2026-08-14T12:22:17.379263Z","title":"Large scale gan training for high fidelity natural image synthesis","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.379263Z"},"links":{"cited_paper":"/paper/1809.11096","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:933325d0f1eef898ba03ea10f798fa9a2fb0c5907c4ad7f716d3f1d2961239a8","observation_id":"19d7b79c-5c74-4f92-88e0-f600e6bffd99","resolution":{"observed_at":"2026-08-14T12:22:17.379263Z","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":"2026-08-14T12:22:18.153256Z","title":"Coco- stuff: Thing and stuff classes in context","venue":null,"work_id":"425062f7-bca2-4780-b8e0-de1624ad8bc6","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.385024Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:a7573a7b04f84fd69b0a9c3093f106e40fbed38b7f150960d204163b179f117e","observation_id":"d259b371-4860-438f-ac5e-fb608c4ae643","resolution":{"observed_at":"2026-08-14T12:22:18.157991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:18.139552Z","title":"Mod- ulating early visual processing by language","venue":null,"work_id":"372804d4-4175-489b-86dc-b4044a021e1e","year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.390490Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:0a11c1022281d768e374f79e14ef442fae28b302b0d7c010260712870b9022bf","observation_id":"31c6c11e-b58f-426e-b262-c5d42b68bd62","resolution":{"observed_at":"2026-08-14T12:22:18.144383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.00704","last_updated":"2017-02-21T18:28:22Z","snapshot_observed_at":"2026-08-14T21:54:30.638570Z","submitted_at":"2016-06-02T14:43:37Z","title":"Adversarially Learned Inference","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.00704","snapshot_observed_at":"2026-08-14T12:22:17.396540Z","title":"Adversarially learned inference","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.396540Z"},"links":{"cited_paper":"/paper/1606.00704","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:50bca7bd7c85e9f0541c445babbbb94cfd966457161ffdfb515a906a80cb1caf","observation_id":"e110ae00-07d8-47ed-8115-e9a56f316979","resolution":{"observed_at":"2026-08-14T12:22:17.396540Z","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":"2026-08-14T12:22:18.125687Z","title":"A learned representation for artistic style","venue":null,"work_id":"604c6ac4-0e89-4e4b-9b9d-561d384ab378","year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.401433Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:a92887bf8db51f9d55a530353c5db3b602e5d87dc1fc59cc10d300ad041da1d7","observation_id":"15a45169-82fc-4130-9121-11faa8f06240","resolution":{"observed_at":"2026-08-14T12:22:18.130708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.406649Z","title":"Generative adversarial nets","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.406649Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:510ef7663c1531244654f24b56abf15ec617b6a5a60e2172936f9e3be6cd44c5","observation_id":"d3596654-e3b0-4ca5-a41f-521608f20969","resolution":{"observed_at":"2026-08-14T12:22:17.406649Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:22:17.411217Z","title":"Mask r-cnn","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.411217Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:ab1b4fba8da9edab8654eb414e5e1fc43f39565c0d4b452ece9110be44201cc8","observation_id":"09b244d2-3330-4cca-a04f-bfa10a959c78","resolution":{"observed_at":"2026-08-14T12:22:17.411217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:22:17.415632Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.415632Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:1563068983bf777fbe4e4d8b4960fcd41d17bbfc405a7e243bc875fc335dc1f1","observation_id":"29eddcb9-048a-46f5-85dc-3f3e713ba46d","resolution":{"observed_at":"2026-08-14T12:22:17.415632Z","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":"2026-08-14T12:22:18.080101Z","title":"GANs trained by a two time-scale update rule converge to a local nash equi- librium","venue":null,"work_id":"0c6fae03-8f78-4919-82f5-22cabe6ff7e6","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.423288Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:378776d5756da56949fd90cb21bbf3aa6c475f709a752389440533cc20174bba","observation_id":"6125b405-0438-4b76-b5a0-e33cdb877b4f","resolution":{"observed_at":"2026-08-14T12:22:18.088581Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:18.066726Z","title":"Gans trained by a two time-scale update rule converge to a local nash equilib- rium","venue":null,"work_id":"a5bab92f-2ff3-46f0-9817-3404bad56da3","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.429411Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:43e473d048fcc08ce0504d126806982b5d93365bf13945554d251d265a9fccb6","observation_id":"dbe18141-b560-4e31-adba-d35f0f004c84","resolution":{"observed_at":"2026-08-14T12:22:18.070987Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1901.00686","last_updated":"2019-01-03T11:18:52Z","snapshot_observed_at":"2026-08-14T17:35:37.015442Z","submitted_at":"2019-01-03T11:18:52Z","title":"Generating Multiple Objects at Spatially Distinct Locations","version":1},"cited_work":{"arxiv_id":"1901.00686","doi":null,"metadata_source":"pith","pith_arxiv_id":"1901.00686","snapshot_observed_at":"2026-08-14T12:22:17.811872Z","title":"Generating Multiple Objects at Spatially Distinct Locations","venue":"cs.CV","work_id":"66879313-222c-424d-9019-f5cec44b3b5e","year":2019},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.434342Z"},"links":{"cited_paper":"/paper/1901.00686","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:619337179030797f47ae4e496827533d6d8ac48d2c6a125aa74125bb77820177","observation_id":"ec9fcf1d-2498-431a-9bbe-fdc87a6f52c2","resolution":{"observed_at":"2026-08-14T12:22:17.816214Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:18.052421Z","title":"Inferring semantic layout for hierarchical text- to-image synthesis","venue":null,"work_id":"e02a6941-c623-4497-80f5-dc23bfdda558","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.440449Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:0266d7dbedea2ffb7b3ffaf61970773ff15dbd7fd67d23a886dedc4b5f867b11","observation_id":"3f2de97d-14eb-4c97-873a-ae68b3831188","resolution":{"observed_at":"2026-08-14T12:22:18.056702Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:18.037729Z","title":"Multimodal unsupervised image-to-image translation","venue":null,"work_id":"9f50e81a-d26b-45b8-8b8d-a768094d02d8","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.444698Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:80a2a0a570a1d515255b65eedf241575c5a3c23ba84907cf4657decde733e425","observation_id":"e4414cec-61aa-48ad-a77a-345f3c6437ab","resolution":{"observed_at":"2026-08-14T12:22:18.041910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1502.03167","last_updated":"2015-03-02T20:44:12Z","snapshot_observed_at":"2026-08-12T21:01:12.961874Z","submitted_at":"2015-02-11T01:44:18Z","title":"Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1502.03167","snapshot_observed_at":"2026-08-14T12:22:17.449518Z","title":"Batch normalization: Accelerating deep network training by reducing internal co- variate shift","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.449518Z"},"links":{"cited_paper":"/paper/1502.03167","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:e3099885f6d771396fa441fe85aefbd042b3381c752fd21f23b6cf44889ee3a0","observation_id":"2305231a-94ec-4382-9833-db8d04f228d0","resolution":{"observed_at":"2026-08-14T12:22:17.449518Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-14T12:22:17.454450Z","title":"Image-to-image translation with conditional adver- sarial networks","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.454450Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:ac9e74fd5165938863b42c4626058a7a772a610015f70fe2f78ce350eedd9293","observation_id":"2bdb2c42-c4f0-43e7-8ddd-17878805ed69","resolution":{"observed_at":"2026-08-14T12:22:17.454450Z","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":"2026-08-14T12:22:18.006875Z","title":"Image gener- ation from scene graphs","venue":null,"work_id":"fda8c1ff-75fb-4a64-94ef-cbd2c15e81e5","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.459182Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:581076f40ccc4e6d679d4e1b4392c20d33837ae823dbaf68aaa9d8ae6cb91bcf","observation_id":"1fef3cb5-135e-41f1-af86-305eb6a09e16","resolution":{"observed_at":"2026-08-14T12:22:18.014036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1710.10196","last_updated":"2018-02-26T15:33:34Z","snapshot_observed_at":"2026-08-15T04:29:56.166616Z","submitted_at":"2017-10-27T15:28:35Z","title":"Progressive Growing of GANs for Improved Quality, Stability, and Variation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1710.10196","snapshot_observed_at":"2026-08-14T12:22:17.463441Z","title":"Progressive growing of gans for improved quality, stability, and variation","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.463441Z"},"links":{"cited_paper":"/paper/1710.10196","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:d927718ab8d6732dbf55b1a91bd3d78dfba654c7e16dd8fdc70bb3c7df6d7c45","observation_id":"975b4e40-7be8-4527-b2bc-a42dbc8a8487","resolution":{"observed_at":"2026-08-14T12:22:17.463441Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1812.04948","last_updated":"2019-03-29T11:08:46Z","snapshot_observed_at":"2026-08-14T17:44:45.577553Z","submitted_at":"2018-12-12T13:59:43Z","title":"A Style-Based Generator Architecture for Generative Adversarial Networks","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1812.04948","snapshot_observed_at":"2026-08-14T12:22:17.469239Z","title":"A style-based generator architecture for generative adversarial networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.469239Z"},"links":{"cited_paper":"/paper/1812.04948","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:c021fe28da0e42da1d577f01acdff28eba7844d349b056596d8e8bf9c0de9142","observation_id":"07d7d5e7-92d5-4cec-8d52-9439b5120ced","resolution":{"observed_at":"2026-08-14T12:22:17.469239Z","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":"2026-08-14T12:22:17.991497Z","title":"Learning to discover cross-domain relations with generative adversarial networks","venue":null,"work_id":"2b528242-4df9-4ab0-b247-160fc8762222","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.473866Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:dae18d2315ce759f5ba34d91c81940be31aef69f5861bf2bd9a2cbd486ab80ec","observation_id":"4f4e908f-6d99-46eb-a1c9-8c8f42e1d59a","resolution":{"observed_at":"2026-08-14T12:22:17.998193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.978912Z","title":"Visual genome: Connecting language and vision using crowdsourced dense image annotations","venue":null,"work_id":"c8d5da7c-8bec-4ee6-8a1e-841ed102e1ad","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.478800Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:12503c7cd222c06a46db205a0635ceef985f13c96961ce242773dff9ca939db2","observation_id":"b3a13f1a-108b-4b4f-b293-7e92dfd7c2fa","resolution":{"observed_at":"2026-08-14T12:22:17.983077Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.10740","last_updated":"2019-02-27T19:25:52Z","snapshot_observed_at":"2026-08-14T17:10:06.300235Z","submitted_at":"2019-02-27T19:25:52Z","title":"Object-driven Text-to-Image Synthesis via Adversarial Training","version":1},"cited_work":{"arxiv_id":"1902.10740","doi":null,"metadata_source":"pith","pith_arxiv_id":"1902.10740","snapshot_observed_at":"2026-08-14T12:22:17.751699Z","title":"Object-driven Text-to-Image Synthesis via Adversarial Training","venue":"cs.CV","work_id":"5db4addf-bbe8-4e4a-b33c-aab50b494ed6","year":2019},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.482605Z"},"links":{"cited_paper":"/paper/1902.10740","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:9051a0f7c2ef5b74305bae88022dd36d28cc9522cf34841c25550c7e61a94a0f","observation_id":"f5dfb9ae-b1c9-4ff4-bddf-4b410819b58a","resolution":{"observed_at":"2026-08-14T12:22:17.757859Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.02894","last_updated":"2017-05-09T01:12:28Z","snapshot_observed_at":"2026-08-14T21:02:09.914348Z","submitted_at":"2017-05-08T14:32:33Z","title":"Geometric GAN","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.02894","snapshot_observed_at":"2026-08-14T12:22:17.488855Z","title":"Geometric gan","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.488855Z"},"links":{"cited_paper":"/paper/1705.02894","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:b096171b4c54262a47bec577847c62be9f5abcf488cf6f3134385455ccd4c948","observation_id":"6c316323-ee28-4c8d-97cc-9b913ff38857","resolution":{"observed_at":"2026-08-14T12:22:17.488855Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.05957","last_updated":"2018-02-16T14:41:39Z","snapshot_observed_at":"2026-08-15T15:47:46.409113Z","submitted_at":"2018-02-16T14:41:39Z","title":"Spectral Normalization for Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.05957","snapshot_observed_at":"2026-08-14T12:22:17.493978Z","title":"Spectral normalization for generative ad- versarial networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.493978Z"},"links":{"cited_paper":"/paper/1802.05957","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:6a4b00e6fec2fb960e13850f02d49ff1613f5f2f86c5a18d121ab27729558f25","observation_id":"ac0635ed-b4fd-4c80-bea1-12dacbafc127","resolution":{"observed_at":"2026-08-14T12:22:17.493978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1802.05637","last_updated":"2018-08-15T00:02:46Z","snapshot_observed_at":"2026-08-14T19:45:30.944638Z","submitted_at":"2018-02-15T16:19:21Z","title":"cGANs with Projection Discriminator","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1802.05637","snapshot_observed_at":"2026-08-14T12:22:17.500390Z","title":"cgans with projection discriminator","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.500390Z"},"links":{"cited_paper":"/paper/1802.05637","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:f6eaa569a87e186086f3841f407e0a1c250725b0c6d29b362830c8993707e3a2","observation_id":"aab1540c-67d4-4662-a499-60224cda21f3","resolution":{"observed_at":"2026-08-14T12:22:17.500390Z","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":"2026-08-14T12:22:17.966501Z","title":"Conditional image synthesis with auxiliary classifier gans","venue":null,"work_id":"d58ff621-5813-4228-bab1-c65dce4160d1","year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.505179Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:d62db1764b6dac82aa1674679ef5a409881415307d79b7e2160ffae054fa4f71","observation_id":"f79109e1-274c-45e6-a249-6e9e4c7dbe42","resolution":{"observed_at":"2026-08-14T12:22:17.971056Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.950576Z","title":"Semantic image synthesis with spatially-adaptive nor- malization","venue":null,"work_id":"0cffdca0-3f18-48b0-8681-d8764b28f7dc","year":null},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.509622Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:463c25bac23ca0e600a34e8a5a178917edd36b8ebd5362307be86142b13cacd0","observation_id":"cc2fdca7-6807-495c-9859-8f6d9fa5b025","resolution":{"observed_at":"2026-08-14T12:22:17.957504Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.06434","last_updated":"2016-01-07T23:09:39Z","snapshot_observed_at":"2026-08-12T18:43:14.431633Z","submitted_at":"2015-11-19T22:50:32Z","title":"Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1511.06434","snapshot_observed_at":"2026-08-14T12:22:17.514327Z","title":"Un- supervised representation learning with deep convolu- tional generative adversarial networks","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.514327Z"},"links":{"cited_paper":"/paper/1511.06434","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:2c29eec8d5abcdb81c6e6e367b48a7b1234e2910eb53c9aa4176939b40f151a6","observation_id":"5f15665f-ef5f-4528-bb6b-33ba07b9e7ab","resolution":{"observed_at":"2026-08-14T12:22:17.514327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1905.10887","last_updated":"2019-10-28T10:49:54Z","snapshot_observed_at":"2026-08-14T16:26:19.209729Z","submitted_at":"2019-05-26T21:41:44Z","title":"Classification Accuracy Score for Conditional Generative Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1905.10887","snapshot_observed_at":"2026-08-14T12:22:17.519665Z","title":"Classification accuracy score for conditional generative models","venue":null,"work_id":null,"year":1905},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.519665Z"},"links":{"cited_paper":"/paper/1905.10887","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:15023b7fca6876f54053132e7558a4c6ce27cc26de2153c9b415fdd9a578eeb7","observation_id":"30db426e-96c7-4fce-b2ef-e142c9d7a066","resolution":{"observed_at":"2026-08-14T12:22:17.519665Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1605.05396","last_updated":"2016-06-05T13:39:27Z","snapshot_observed_at":"2026-08-14T21:56:56.378295Z","submitted_at":"2016-05-17T23:09:15Z","title":"Generative Adversarial Text to Image Synthesis","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.05396","snapshot_observed_at":"2026-08-14T12:22:17.525032Z","title":"Genera- tive adversarial text to image synthesis","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.525032Z"},"links":{"cited_paper":"/paper/1605.05396","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:9537c1f24c44c4d71f180efa4da578bee08980922b494522e4c97ec7035e757e","observation_id":"952bb138-4e18-4ce3-8fd6-5ca81be32377","resolution":{"observed_at":"2026-08-14T12:22:17.525032Z","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":"2026-08-14T12:22:17.938769Z","title":"Improved techniques for training gans","venue":null,"work_id":"3508992f-04fa-4a7b-b565-29637817f9d7","year":2016},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.529688Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:06bdcb622195777de73ea536042bf9a2f042409c8bc586b62df58aac53ff76cb","observation_id":"4aa764ae-748f-44b6-b3c6-84551d00d474","resolution":{"observed_at":"2026-08-14T12:22:17.942585Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.925178Z","title":"Going deeper with convolutions","venue":null,"work_id":"d191eefa-2dcf-4792-a33b-eae8ee008257","year":2015},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.535746Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:e24387ea71f00489127bb87f5243d52c3e9d31091f4faebd3a509b65b4095856","observation_id":"1fd3a022-0485-4f7c-b706-f3038d7bd4fb","resolution":{"observed_at":"2026-08-14T12:22:17.930015Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1702.08896","last_updated":"2017-11-05T01:52:45Z","snapshot_observed_at":"2026-08-14T21:14:18.903574Z","submitted_at":"2017-02-28T18:33:32Z","title":"Hierarchical Implicit Models and Likelihood-Free Variational Inference","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1702.08896","snapshot_observed_at":"2026-08-14T12:22:17.539897Z","title":"Deep and hierarchical implicit models","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.539897Z"},"links":{"cited_paper":"/paper/1702.08896","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:cfdee721c2525c9fb577301025e6f9527a627cb64b47676daaeeb324935a6076","observation_id":"62f5b399-45ce-4a2d-91f8-40f5ef4d9d86","resolution":{"observed_at":"2026-08-14T12:22:17.539897Z","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":"2026-08-14T12:22:17.910604Z","title":"High-resolution image syn- thesis and semantic manipulation with conditional gans","venue":null,"work_id":"8e1959f1-ba6d-443e-80b8-1c7225a05cbf","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.544379Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:96ecb5d8d6da8ea9b7d1d4e768da29a15cada8ded5735bffcff040947991982f","observation_id":"cf027fbb-920c-482c-a9a3-96b5f988ca8b","resolution":{"observed_at":"2026-08-14T12:22:17.915356Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.896726Z","title":"Attngan: Fine- grained text to image generation with attentional generative adversarial networks","venue":null,"work_id":"d5ff35c8-ae1b-4da9-a68a-d3c0df6448a4","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.549236Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:5a99746f2db422be89cdef74b168da8131b4079b31092f8ec844bb94cc23d56b","observation_id":"52aebf67-a335-42ea-aa18-d7c3f8f30c7a","resolution":{"observed_at":"2026-08-14T12:22:17.901751Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.08318","last_updated":"2019-06-14T18:20:10Z","snapshot_observed_at":"2026-08-15T09:55:20.680511Z","submitted_at":"2018-05-21T23:10:35Z","title":"Self-Attention Generative Adversarial Networks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1805.08318","snapshot_observed_at":"2026-08-14T12:22:17.553484Z","title":"Self-attention generative adversarial networks","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.553484Z"},"links":{"cited_paper":"/paper/1805.08318","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:d75431cb57f2942528e23efde17ee7181b9a3c6fda9ef412f8e17537e0f9506d","observation_id":"cda41ae9-d919-4371-914a-6470c0350769","resolution":{"observed_at":"2026-08-14T12:22:17.553484Z","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":"2026-08-14T12:22:17.882261Z","title":"Stack- gan: Text to photo-realistic image synthesis with stacked generative adversarial networks","venue":null,"work_id":"70dad254-ccc2-440a-9ba4-cf3273302e4c","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.558021Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:8c6137be96985136cd72d7fb212557a5d4cf67c0312a109c9d19e5639256f230","observation_id":"5ffa1038-d110-449e-a112-8e2af2f19d53","resolution":{"observed_at":"2026-08-14T12:22:17.888293Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.868132Z","title":"The unreasonable effectiveness of deep features as a perceptual metric","venue":null,"work_id":"9e107983-6f61-4fe6-bc02-530d58615d63","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.562179Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:f64817ffd1f8ea34d1525ab2b1d5ed8cf2b169531453116147cf6b5aebebb3c4","observation_id":"594359ce-bb2c-410a-9b8d-9e5d2b5a10ec","resolution":{"observed_at":"2026-08-14T12:22:17.872777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1811.11389","last_updated":"2019-10-14T21:17:06Z","snapshot_observed_at":"2026-08-14T17:52:15.954770Z","submitted_at":"2018-11-28T05:11:14Z","title":"Image Generation from Layout","version":3},"cited_work":{"arxiv_id":"1811.11389","doi":null,"metadata_source":"pith","pith_arxiv_id":"1811.11389","snapshot_observed_at":"2026-08-14T12:22:17.607762Z","title":"Image Generation from Layout","venue":"cs.CV","work_id":"21ecb03b-3c22-4e8d-9b2e-eaef57ce94f0","year":2018},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.566502Z"},"links":{"cited_paper":"/paper/1811.11389","citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:ce2002c87ed68c17d141db6aabecf48eedf0e40a970b880df94e00d523f05f13","observation_id":"8b85019d-ea6d-47ef-aadb-e4e97452ab27","resolution":{"observed_at":"2026-08-14T12:22:17.614291Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+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":"2026-08-14T12:22:17.851960Z","title":"Unpaired image-to-image translation using cycle- consistent adversarial networks","venue":null,"work_id":"c7aa7215-de02-41e0-a297-0bea051d26d4","year":2017},"citing_paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-14T12:22:17.571336Z"},"links":{"citing_paper":"/paper/1908.07500"},"observation_digest":"sha256:152a99e9a23a7d3ecfa72d42aafc8016bfb003f336813b9b431028619c28e8de","observation_id":"b0356d2a-434a-4bcf-9f91-2926941a0bde","resolution":{"observed_at":"2026-08-14T12:22:17.857590Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"1908.07500","last_updated":"2019-08-20T17:22:31Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-15T09:54:26.600678Z","submitted_at":"2019-08-20T17:22:31Z","title":"Image Synthesis From Reconfigurable Layout and Style"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":17,"verified_exact":3,"verified_fuzzy":19},"total_outbound_references":39},"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":"2026-08-16T06:30:59.297886+00:00","source":"crossref"},{"observed_at":"2026-08-16T06:30:54.164669+00:00","source":"retraction_watch"}],"thesis":"As of 16 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 0 inbound Pith citation observations for arXiv:1908.07500."}