{"as_of":"2026-08-07T22:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:52021865767d611999a68d87156e618054a28bba281061b3f7509bd640d34f8b","coverage":[{"denominator":80,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":80,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T22:21:08.251956Z","state":"measured"},{"denominator":80,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":80,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+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/2506.21925/citation-record","integrity":"/paper/2506.21925/integrity","json":"/paper/2506.21925/citation-record.json","paper":"/paper/2506.21925"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T22:21:17.949893Z","title":"Generative adversarial nets,","venue":null,"work_id":"8764e0e2-d94d-4683-a822-40f1b2ade3d3","year":2014},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T22:19:50.689236Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:c517434e67415f076f99c47eac591f2652723b9911b688da855978f58c3b1bc6","observation_id":"41724e7f-8d69-48c9-b153-acf498382f65","resolution":{"observed_at":"2026-08-06T22:21:17.993922Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6114","last_updated":"2022-12-10T21:04:00Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2013-12-20T20:58:10Z","title":"Auto-Encoding Variational Bayes","version":11},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6114","snapshot_observed_at":"2026-08-06T22:19:51.583672Z","title":"Auto-Encoding Variational Bayes,","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T22:19:51.583672Z"},"links":{"cited_paper":"/paper/1312.6114","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:da687b757c42f6fb69451fe54addeb47924dedbe3adabefb59f292a24ab3f90c","observation_id":"18f1db29-9785-471d-8a0d-175c2743737e","resolution":{"observed_at":"2026-08-06T22:19:51.583672Z","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":"2026-08-06T22:21:17.780160Z","title":"High- resolution image synthesis with latent diffusion models,","venue":null,"work_id":"c3a10e22-c31e-43bb-891a-54dfdd3ef91c","year":null},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T22:19:54.419733Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:7aac2db3ab3888bc3fd733d420af9187a7a8a14a96483dacc421aa0e0e69a233","observation_id":"0299e21d-8efa-47f3-ae9e-8060f6b4d399","resolution":{"observed_at":"2026-08-06T22:21:17.881027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:17.573731Z","title":"Learning transferable visual models from natural language supervi- sion,","venue":null,"work_id":"fc2695c7-51f7-4f6f-a769-a350b4e8adf4","year":null},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T22:19:54.642921Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:7bbf5c2bc14478d5da8b44c5b63d7c0bccc54665b0aa76df0ca145eceb71e56f","observation_id":"811254a8-3a4b-46ee-8f16-a1895799a5a4","resolution":{"observed_at":"2026-08-06T22:21:17.673507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.12597","last_updated":"2023-06-15T07:57:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-01-30T00:56:51Z","title":"BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2301.12597","snapshot_observed_at":"2026-08-06T22:19:55.039591Z","title":"Blip-2: Bootstrapping language- image pre-training with frozen image encoders and large language models,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T22:19:55.039591Z"},"links":{"cited_paper":"/paper/2301.12597","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:5c07c371f1b6ca7b37f2ae52caba74e5e100ece2386ef24633e585e0ca569f09","observation_id":"b7ca5aa4-620d-4b55-af43-183e5cea8d9c","resolution":{"observed_at":"2026-08-06T22:19:55.039591Z","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":"2026-08-06T22:21:17.387673Z","title":"MVDiffusion: Enabling holistic multi-view image generation with correspondence- aware diffusion,","venue":null,"work_id":"5bc3bbba-6c73-4340-8290-c23cecc3cfa5","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:11.924152Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:bac802b640242dca81a282b30c3194dfce5c73d15b5688e454c44ed20c82cb7a","observation_id":"2ea0338d-6d5e-4769-894f-7d1f2e58a93a","resolution":{"observed_at":"2026-08-06T22:21:17.472848Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:20:12.687175Z","title":"Text2light: Zero-shot text-driven hdr panorama generation,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.687175Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:a9d7b7deb238e5b61e97a0a8eeb8bcba229a60b1ac29bc0e0f5fb2df3caca1c3","observation_id":"1739e202-c583-4c9b-9334-48df2428a728","resolution":{"observed_at":"2026-08-06T22:20:12.687175Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.06903","last_updated":"2024-07-25T08:19:53Z","snapshot_observed_at":"2026-07-06T17:58:12.766206Z","submitted_at":"2024-04-10T10:46:59Z","title":"DreamScene360: Unconstrained Text-to-3D Scene Generation with Panoramic Gaussian Splatting","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.06903","snapshot_observed_at":"2026-08-06T22:20:12.734669Z","title":"Dreamscene360: Unconstrained text-to- 3d scene generation with panoramic gaussian splatting,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.734669Z"},"links":{"cited_paper":"/paper/2404.06903","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:e8d0dbb0663d8b3cd1ca382740cb4ae195d2f37fcc1234fe8d93ecad931e8313","observation_id":"9871a7b0-8f97-456f-9bcc-97be835065b3","resolution":{"observed_at":"2026-08-06T22:20:12.734669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13527","last_updated":"2024-10-03T06:26:49Z","snapshot_observed_at":"2026-07-06T18:33:41.653334Z","submitted_at":"2024-06-19T13:11:02Z","title":"4K4DGen: Panoramic 4D Generation at 4K Resolution","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13527","snapshot_observed_at":"2026-08-06T22:20:12.785334Z","title":"4k4dgen: Panoramic 4d generation at 4k resolution,","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.785334Z"},"links":{"cited_paper":"/paper/2406.13527","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:11e76240600dac7a408cb777ed064107810d112061101dedaeef50d61e488130","observation_id":"140fbcc0-7718-4136-a1b5-e7e3bc1d1c42","resolution":{"observed_at":"2026-08-06T22:20:12.785334Z","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":"2026-08-06T22:21:17.233545Z","title":"GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium,","venue":null,"work_id":"4bc6752b-b45d-4ad8-bc52-3eed006ae735","year":2017},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.800603Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:fac7dcd541a1529f5224be681f43cf93351aae3a9652709776d8676b402768cd","observation_id":"5cd5f489-bbe7-4bc7-8997-0da976537d26","resolution":{"observed_at":"2026-08-06T22:21:17.292457Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:17.132262Z","title":"Improved techniques for training gans,","venue":null,"work_id":"c0e38099-50ac-490e-b50f-34de6f768f7a","year":2016},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.821396Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:8c24a273757a459758555d4d10458969f3afd18a26b7946066bd7f2fbd0de232","observation_id":"1f944fe1-08eb-496b-a9c2-aa213d7f9ed9","resolution":{"observed_at":"2026-08-06T22:21:17.180795Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2104.08718","last_updated":"2022-03-23T19:47:21Z","snapshot_observed_at":"2026-07-06T11:01:02.207193Z","submitted_at":"2021-04-18T05:00:29Z","title":"CLIPScore: A Reference-free Evaluation Metric for Image Captioning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.08718","snapshot_observed_at":"2026-08-06T22:20:12.855434Z","title":"Clipscore: A reference-free evaluation metric for image captioning,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.855434Z"},"links":{"cited_paper":"/paper/2104.08718","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:8bda757ee29ad5a800cdf477638eb01c67c08dc406cb7bb6e67c65a4866dddff","observation_id":"ff702d6d-2c10-438e-9276-43936340cdd2","resolution":{"observed_at":"2026-08-06T22:20:12.855434Z","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":"2026-08-06T22:21:16.984016Z","title":"Aigciqa2023: A large-scale image quality assessment database for ai generated images: from the perspectives of quality, authenticity and correspondence,","venue":null,"work_id":"83663dbc-fcb6-4842-a761-d111e753fdb2","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.875731Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:8a6af216d78032f1f0f81a9b5f940493ec29b88db2867176e4f64243adfdc2b9","observation_id":"1e7d1bd9-35d8-4814-b79d-e8df86bf312d","resolution":{"observed_at":"2026-08-06T22:21:17.066086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.869091Z","title":"Agiqa-3k: An open database for ai-generated image quality assessment,","venue":null,"work_id":"e48f51f5-897b-452e-b678-433a67172721","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.896649Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:c14ce8a5a1015052004edf169c3e58b38c036f014ebc7e916a53099a9062f383","observation_id":"2a0ad9cb-35ff-4775-b52b-45582f5b38e1","resolution":{"observed_at":"2026-08-06T22:21:16.912393Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.758829Z","title":"Sgdnet: An end-to-end saliency-guided deep neural network for no-reference image quality assessment,","venue":null,"work_id":"588f5074-a6e1-426e-85e1-5a4fa6294401","year":2019},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.914493Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:78b9a745b61221c4b9296587e8594561d3f9a0fa1eb6b31ebfc051b4a8e6ddad","observation_id":"ed593c32-1573-4e50-9a1e-773919a13786","resolution":{"observed_at":"2026-08-06T22:21:16.794572Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.609642Z","title":"Realistic saliency guided image enhancement,","venue":null,"work_id":"e5dd8069-9a95-40ef-a67d-9cfd69629ad9","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.939015Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:3ccd42b036ab99edead9573448519e44929c9b56e170fd70649f3e2647e6a72e","observation_id":"69ea30b2-7b3d-4df1-bce4-05794d281f41","resolution":{"observed_at":"2026-08-06T22:21:16.718619Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.391802Z","title":"Rich human feedback for text-to-image generation,","venue":null,"work_id":"edc84407-9ee7-4704-bbe9-f39a70043637","year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:12.974909Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:3c545eb844542b8cb99ad845ccce78f9d4447930558fe1d674635343d1cc2d32","observation_id":"dc8dfb79-4aa3-4da9-ae70-e9574f12226b","resolution":{"observed_at":"2026-08-06T22:21:16.485185Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.194937Z","title":"Mc360iqa: A multi-channel cnn for blind 360-degree image quality assessment,","venue":null,"work_id":"d0919ba9-b7c6-4012-ab8a-3138bd652f98","year":2019},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.012712Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:875023a0b918bf1e0ad1368f05a3e95e28e4935c33dc0285b32e172da947bb63","observation_id":"fe2a7ad6-82e0-444c-8e0c-c164cd5c1160","resolution":{"observed_at":"2026-08-06T22:21:16.285128Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:16.048177Z","title":"Perceptual quality assessment of omnidirectional images,","venue":null,"work_id":"d3161645-18a8-436a-b181-696f7a3835a3","year":2018},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.053697Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:f350874829cdeffbda1c14709e431cb53ce3dabe1768a0b3b91a3c75188652e5","observation_id":"cf026fc1-871a-4db6-926e-560c01011855","resolution":{"observed_at":"2026-08-06T22:21:16.129789Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.864348Z","title":"Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment,","venue":null,"work_id":"43788bfa-4933-4aa0-8e00-ccc66a522ef2","year":2020},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.104827Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:041b02cda9f330ba10ff6f8cc82fb4d0c4d95e27ed489bab255042976cf7d2b5","observation_id":"a700a177-8d24-4661-b469-c74bf1da46a5","resolution":{"observed_at":"2026-08-06T22:21:15.946210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.723422Z","title":"Perceptual quality as- sessment of smartphone photography,","venue":null,"work_id":"17115f57-9bd1-4d55-b34d-dae570f70118","year":2020},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.153776Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:9a7eff300e495aafe282f2e998e017c73fb28d48e5430116acca2d5dba3b3f13","observation_id":"c6c0e33e-2929-4167-930e-9f5a46a094e7","resolution":{"observed_at":"2026-08-06T22:21:15.759052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.603760Z","title":"Perceptual Quality Assessment of Omnidirectional Audio- Visual Signals,","venue":null,"work_id":"37b94147-5962-4688-aa49-5e0bee1c91e8","year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.234189Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:f14691f9c100508603c3ba8370a0bd45d439114dfc35814001272303bbc9782d","observation_id":"bbfb66f2-fe00-433e-b087-558242685d41","resolution":{"observed_at":"2026-08-06T22:21:15.662012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.322451Z","title":"Confusing image quality assessment: Toward better augmented reality experience,","venue":null,"work_id":"fdf62fce-5d2c-4aad-99c9-37f785164f48","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.304749Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:99cc9a2115f123bf02583add15ae7cbf3d8454310f2a0586afc301cacdd0c3f8","observation_id":"347fd472-19df-414e-bf5c-c8f8b89dd4f1","resolution":{"observed_at":"2026-08-06T22:21:15.498755Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21363","last_updated":"2025-02-21T06:56:59Z","snapshot_observed_at":"2026-07-06T18:54:54.118506Z","submitted_at":"2024-07-31T06:20:21Z","title":"ESIQA: Perceptual Quality Assessment of Vision-Pro-based Egocentric Spatial Images","version":2},"cited_work":{"arxiv_id":"2407.21363","doi":null,"metadata_source":"pith","pith_arxiv_id":"2407.21363","snapshot_observed_at":"2026-08-06T22:21:08.942180Z","title":"ESIQA: Perceptual Quality Assessment of Vision-Pro-based Egocentric Spatial Images","venue":"cs.CV","work_id":"42e0e46b-9d93-46c9-b6e6-599cadecde65","year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.368441Z"},"links":{"cited_paper":"/paper/2407.21363","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:255a31fa200477e0b6da0a73c72037418554741d98eb219d26968ceeeef9278c","observation_id":"6fdf826a-7b76-42f5-b08b-8894b6229c5d","resolution":{"observed_at":"2026-08-06T22:21:09.002471Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.07346","last_updated":"2025-02-02T08:58:09Z","snapshot_observed_at":"2026-07-06T18:13:16.171803Z","submitted_at":"2024-05-12T17:45:11Z","title":"Quality Assessment for AI Generated Images with Instruction Tuning","version":2},"cited_work":{"arxiv_id":"2405.07346","doi":null,"metadata_source":"pith","pith_arxiv_id":"2405.07346","snapshot_observed_at":"2026-08-06T22:21:08.798105Z","title":"Quality Assessment for AI Generated Images with Instruction Tuning","venue":"cs.CV","work_id":"25c912cb-3d24-4c37-a41b-96ee21eb428e","year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.437257Z"},"links":{"cited_paper":"/paper/2405.07346","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:50c7e26fab480f05313dcf4712faa6d4760bdbf14b19012f153223f90c29f14f","observation_id":"49ffbcf3-9504-45d3-bba6-c230d2fb273b","resolution":{"observed_at":"2026-08-06T22:21:08.844950Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.192915Z","title":"Salicon: Saliency in context,","venue":null,"work_id":"933d22e2-8156-4ef5-be96-02cfb1adb97b","year":2015},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.477062Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:b13d32c81d891de70bfef4fb67e5784a4a56edd3d62d86e4085359c7168b1cd2","observation_id":"2c8dba25-3516-4c7b-9837-bcc952cc9b68","resolution":{"observed_at":"2026-08-06T22:21:15.269332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1505.03581","last_updated":"2015-05-14T00:34:43Z","snapshot_observed_at":"2026-07-06T04:17:49.006000Z","submitted_at":"2015-05-14T00:34:43Z","title":"CAT2000: A Large Scale Fixation Dataset for Boosting Saliency Research","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1505.03581","snapshot_observed_at":"2026-08-06T22:20:13.556307Z","title":"Cat2000: A large scale fixation dataset for boosting saliency research,","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.556307Z"},"links":{"cited_paper":"/paper/1505.03581","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:20d30e31b4b1d4a04d3fc8efa591331cdab82dee3df830559bf254fef1acb590","observation_id":"d3369cca-51a3-4602-935b-e4bb039b0b8c","resolution":{"observed_at":"2026-08-06T22:20:13.556307Z","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":"2026-08-06T22:21:14.858218Z","title":"Saliency based on information maximization,","venue":null,"work_id":"c357b704-d943-4090-8db2-3d22f58839ad","year":2005},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.604107Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:8eb1e27d1895dfbd6ae4786c68f187586b8c62e6271cc95c3951ab1906c8201a","observation_id":"1d7710c9-9371-4fae-9a14-6f105921616a","resolution":{"observed_at":"2026-08-06T22:21:14.940474Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.684363Z","title":"Predicting human gaze using low-level saliency combined with face detection,","venue":null,"work_id":"69378d2f-cd3c-40ed-85ff-9da58a446dcc","year":2007},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.648584Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:b05325efee3e4c441bac09d8b3649ae58f0d6db10e35f0469d095414719ef176","observation_id":"878fb682-4634-4dd3-9290-d6897d7a3cfb","resolution":{"observed_at":"2026-08-06T22:21:14.758973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.547989Z","title":"Visual saliency estimation by nonlinearly integrating features using region covariances,","venue":null,"work_id":"755f726e-71a9-4e8e-9855-d16ef1b9f7c2","year":2013},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.719388Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:79828f6c63637eadbeaebcd3e3c0df30d1486168e09169e17eee79d1eb039023","observation_id":"eb723941-ca67-4100-ac26-3b7140fbdf5a","resolution":{"observed_at":"2026-08-06T22:21:14.609829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.389944Z","title":"Saliency in augmented reality,","venue":null,"work_id":"4739c3cb-aa0c-4782-8dd5-f3e2dfbcd5ac","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.775041Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:367f890af0143b535d1bd7ea8e819efb02c0ccf97d5c5c2c1dffc09220f5ed57","observation_id":"731eb68f-875e-4d6f-bb8a-675bf0289c09","resolution":{"observed_at":"2026-08-06T22:21:14.451796Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.296491Z","title":"Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks,","venue":null,"work_id":"1e3af441-8a85-4353-ab30-ee6f7c98755b","year":2015},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.827170Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:eac146d5a8470e76f61d34fa0a46c747a16e3f5727c2bfca776549814aa92358","observation_id":"5695e36a-f080-49b7-8b8c-3408db5a468a","resolution":{"observed_at":"2026-08-06T22:21:14.339824Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.177721Z","title":"Predicting human eye fixations via an lstm-based saliency attentive model,","venue":null,"work_id":"37ed7433-ec39-4588-9ee5-79a930475dd5","year":2018},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.897980Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:34f998b00692a952e9a2095ea953fdfabf37a3693e83a85383fd5c5d3d37e7cf","observation_id":"99982fd3-a5f9-4a41-ae07-1e91ebfbbbfd","resolution":{"observed_at":"2026-08-06T22:21:14.225733Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:14.093056Z","title":"Visual attention analysis and prediction on human faces for children with autism spectrum disorder,","venue":null,"work_id":"4776b0d2-d7e1-4b5b-80c7-3e512e102c11","year":2019},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.938944Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:c50dfda2b52634424ad160eef3de3511b21c0d99ee99f22857ea592e3e1f88f1","observation_id":"92e45de5-8747-4622-bef8-4397fd94cab4","resolution":{"observed_at":"2026-08-06T22:21:14.133754Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.953785Z","title":"A dataset of eye movements for the children with autism spectrum disorder,","venue":null,"work_id":"b4ae24d7-211e-414b-b672-cb1bee511201","year":2019},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:13.993007Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:c74dd92dde3738ca0fb966980bdd07a6bf2cbfd5ac62adc34f847a5f77c1225f","observation_id":"298af49c-fd9e-47c6-87f1-2ac28af309dd","resolution":{"observed_at":"2026-08-06T22:21:14.029300Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03413","last_updated":"2024-02-05T16:13:52Z","snapshot_observed_at":"2026-07-31T05:37:15.555956Z","submitted_at":"2024-02-05T16:13:52Z","title":"Perceptual Video Quality Assessment: A Survey","version":1},"cited_work":{"arxiv_id":"2402.03413","doi":null,"metadata_source":"pith","pith_arxiv_id":"2402.03413","snapshot_observed_at":"2026-08-06T22:21:08.564896Z","title":"Perceptual Video Quality Assessment: A Survey","venue":"cs.MM","work_id":"431eeae3-787a-4718-93bc-4b934c599bf2","year":2024},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.049743Z"},"links":{"cited_paper":"/paper/2402.03413","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:be495ecf8a020052e0325f038715038517274f7125bace65ae85b654926c7c36","observation_id":"faf96921-311d-4aa7-a2a6-43ffe1d3aec3","resolution":{"observed_at":"2026-08-06T22:21:08.615147Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.867486Z","title":"Blind image quality assessment: A fuzzy neural network for opinion score distribution prediction,","venue":null,"work_id":"a53bc405-49ea-4951-9034-a2c2252bfcd5","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.079567Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:35266f43ee157ff1294301872088a38edda10e83a98a479ff02ba68c38d2cdec","observation_id":"36c91440-fb96-4476-b6fc-bae166de4d48","resolution":{"observed_at":"2026-08-06T22:21:13.912617Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.734548Z","title":"Identifying children with autism spectrum disorder based on gaze-following,","venue":null,"work_id":"58ac4ee1-bc5c-4a02-8860-438bb19c868f","year":2020},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.144754Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:ed535949b7d11583e790f8d800867bd11901103d0d05c5f89621117c8d6ac102","observation_id":"03b4d84e-a57c-4e63-8cf6-aa573c3c4f58","resolution":{"observed_at":"2026-08-06T22:21:13.783743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.597342Z","title":"Matterport3d: Learning from rgb- d data in indoor environments,","venue":null,"work_id":"352adeab-4b08-4d8c-8f82-ff96f26da639","year":2017},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.236500Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:d5df8abb262cf6231c7d8b27f63157660d160ea43d4d733bb70d70c344635430","observation_id":"f3d7d44c-3b36-42a7-93c1-5635bec0ab73","resolution":{"observed_at":"2026-08-06T22:21:13.667785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.530827Z","title":"Recognizing scene viewpoint using panoramic place representation,","venue":null,"work_id":"3734a377-5e7b-4365-93f1-b360d74aad44","year":2012},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.307387Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:a05816ecbb2f51c0ded53071c899dc734e1c2fb2e277e1ad8a2dc148b759c608","observation_id":"22c7bd84-153a-4dce-b0f6-16d1f43e4c7d","resolution":{"observed_at":"2026-08-06T22:21:13.567012Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.06125","last_updated":"2022-04-13T01:10:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-04-13T01:10:33Z","title":"Hierarchical Text-Conditional Image Generation with CLIP Latents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.06125","snapshot_observed_at":"2026-08-06T22:20:14.427950Z","title":"Hierarchical text-conditional image generation with clip latents,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.427950Z"},"links":{"cited_paper":"/paper/2204.06125","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:4c0c4fb386c614e6b2e10fd85fe291c6f298eb174ae9430877c4917c1fa909f7","observation_id":"19f3b7ef-e0d1-4e6b-8381-3dbecf1e336f","resolution":{"observed_at":"2026-08-06T22:20:14.427950Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2302.01133","last_updated":"2023-05-30T08:52:45Z","snapshot_observed_at":"2026-08-06T09:54:34.260823Z","submitted_at":"2023-02-02T14:47:19Z","title":"SceneScape: Text-Driven Consistent Scene Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.01133","snapshot_observed_at":"2026-08-06T22:20:14.522241Z","title":"Scenescape: Text- driven consistent scene generation,","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.522241Z"},"links":{"cited_paper":"/paper/2302.01133","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:4f3be0b0366381b44aa36c0084f5a727c94d92391c7cf18c67e1696902b28eca","observation_id":"d867da9f-e5e6-4a65-b79c-ab2d2cfb5cc9","resolution":{"observed_at":"2026-08-06T22:20:14.522241Z","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":"2026-08-06T22:21:13.359112Z","title":"High- resolution image synthesis with latent diffusion models,","venue":null,"work_id":"eeed8f20-43e8-4a41-adc6-4665c04881d0","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.588657Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:d3625ec033897055cdee1d1f9a0555dec4f6675d106645669f3f6971e63c91da","observation_id":"f24aea2e-d944-47de-9461-36c5cdaed324","resolution":{"observed_at":"2026-08-06T22:21:13.445658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.05190","last_updated":"2023-11-09T08:03:40Z","snapshot_observed_at":"2026-07-06T16:45:03.211791Z","submitted_at":"2023-11-09T08:03:40Z","title":"Audio-visual Saliency for Omnidirectional Videos","version":1},"cited_work":{"arxiv_id":"2311.05190","doi":null,"metadata_source":"pith","pith_arxiv_id":"2311.05190","snapshot_observed_at":"2026-08-06T22:21:08.362414Z","title":"Audio-visual Saliency for Omnidirectional Videos","venue":"cs.CV","work_id":"356ee1b2-cf61-49f7-9a51-05661b33f964","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.661333Z"},"links":{"cited_paper":"/paper/2311.05190","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:9bff4ddc74569dde11551b9502b025636a163a3c9079e9502fbd4119ab6ef0a7","observation_id":"fe364f3f-5eae-4300-896c-9c3209c70ed7","resolution":{"observed_at":"2026-08-06T22:21:08.405178Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.199405Z","title":"Attentive deep image quality assessment for omnidirectional stitching,","venue":null,"work_id":"bfe0471d-9ef3-467f-80de-da4fe987cb5a","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.754270Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:3f40e0b0e72ce224c0c53e4a46166362897c3f95913616eed7d238b34f6b3f35","observation_id":"7011bae5-7936-45c9-9f3f-dafa5d8539f5","resolution":{"observed_at":"2026-08-06T22:21:13.290325Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:13.059123Z","title":"Augmented reality image quality assessment based on visual confusion theory,","venue":null,"work_id":"d0d56942-f386-4111-a06d-28f7b8a7de09","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.834852Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:cde70da004ffc48d344a3073db4501a89c1b3db7ce3353f0f986c1fe2e61a0a7","observation_id":"dff0d7f1-af25-4340-a194-0e71d9adca3e","resolution":{"observed_at":"2026-08-06T22:21:13.130045Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:12.832239Z","title":"Viewing behavior supported visual saliency predictor for 360 degree videos,","venue":null,"work_id":"b0b099a5-ab4f-4c4e-9a9d-fa0a740c82ee","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:14.945107Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:6cc3460125b7c968449153d9d580f4bab1eebd46b0d4bc24ea9bb9fe2684a3bc","observation_id":"1ae268f1-e4fa-4f59-835a-0f79dcd61017","resolution":{"observed_at":"2026-08-06T22:21:12.872650Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:12.699797Z","title":"Ivqad 2017: An immersive video quality assessment database,","venue":null,"work_id":"b8588d92-757d-41b4-9cf3-adf74b2d378d","year":2017},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.016080Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:2a633f7e1d00230f07aadc804e74622486bf438ce9079f7abe12ed736b950b9d","observation_id":"6887c6b3-56bb-4ce4-bae1-0829eab68d7b","resolution":{"observed_at":"2026-08-06T22:21:12.780189Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:12.513866Z","title":"Methodology for the subjective assessment of the quality of television pictures,","venue":null,"work_id":"46fa1e49-f34a-4a88-b648-e7b053326dc1","year":2012},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.106064Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:4d9920a253cbe7abb1f24ef1a341fcca0847f839c6944d8f3000a607c66fd54c","observation_id":"254a772d-4656-4edd-ba36-ce6c0e40c668","resolution":{"observed_at":"2026-08-06T22:21:12.586400Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:12.213741Z","title":"How is gaze influenced by image transformations? dataset and model,","venue":null,"work_id":"4caae4c7-59a3-4aea-82c5-0c4db64a8e58","year":2019},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.212481Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:5dfb6e8cefc45a24646d0daa8dc08d57c15f0d24602fe5987353d690fb6a1078","observation_id":"07a5f239-1f7a-48af-9359-b44258630d1b","resolution":{"observed_at":"2026-08-06T22:21:12.361272Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:12.069014Z","title":"Perceptual quality assessment of omnidirectional images as moving camera videos,","venue":null,"work_id":"a40d45b8-3a6d-466d-9146-e04c98d254c7","year":2021},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.362422Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:fe0c8656feb1067742b1c57560ef849b25d0964c4d35f2aed95d5206992fc4ef","observation_id":"629f932e-8593-4ca9-b060-c4dd10f8784f","resolution":{"observed_at":"2026-08-06T22:21:12.132935Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.790717Z","title":"Learning without human scores for blind image quality assessment,","venue":null,"work_id":"38e70cdc-7851-4e02-b3f4-2763fde572a9","year":null},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.499841Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:94b30365ef77ccb93fa33a2316f9ad268bb6aa246b69b03a875b224c8d740499","observation_id":"3e8dc69c-3f77-449b-8f00-ac9bb0df0768","resolution":{"observed_at":"2026-08-06T22:21:11.943426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.695586Z","title":"Blind image quality esti- mation via distortion aggravation,","venue":null,"work_id":"53f42bc4-3b3b-4a5f-bd83-13329319fb2a","year":2018},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.603420Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:759abab7daa1e190263c3ccd4f6066ddc52399edacab4963b326ce812f2534c2","observation_id":"38379481-2483-4e47-8c00-b06f81cb8a95","resolution":{"observed_at":"2026-08-06T22:21:11.741547Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:20:15.704376Z","title":"Making a “completely blind","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.704376Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:08cc636f4a5142edaf361b674d8e447f2c258385ffadb930b94b247b4a85f17f","observation_id":"33d310e0-c924-4189-9265-ac95a45a1f73","resolution":{"observed_at":"2026-08-06T22:20:15.704376Z","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":"2026-08-06T22:21:11.555068Z","title":"A feature-enriched completely blind image quality evaluator,","venue":null,"work_id":"ea086663-e192-4507-bd94-1994b297389e","year":2015},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.795338Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:90b547a8f1aaf3cc1bbb531c8ab8149b90be447614b55337f111ed8d0972868f","observation_id":"22d96f35-45f4-4f30-b00e-c4f901ad6716","resolution":{"observed_at":"2026-08-06T22:21:11.617689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.412717Z","title":"Blind image quality assessment based on high order statistics aggregation,","venue":null,"work_id":"226f525f-29f2-4110-b625-d61d4fb5fb5f","year":2016},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.875612Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:8f11b42c53b59cfa232b86d746c202e9909622c00e3b7ae1e82eb8cf01c3bdbe","observation_id":"3799d258-a256-4194-90d5-93242583e6c2","resolution":{"observed_at":"2026-08-06T22:21:11.484926Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.351782Z","title":"Blind quality assessment based on pseudo-reference image,","venue":null,"work_id":"3d992f40-83e9-4c3b-adf1-f563df42afee","year":2018},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.953831Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:690149576bd30b20a529485e8ce059356c2a06975052c8d6ad102d9a8900d490","observation_id":"b7040921-c294-4aa2-95cf-b68bb4e82612","resolution":{"observed_at":"2026-08-06T22:21:11.383291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.242849Z","title":"Fisblim: A five-step blind metric for quality assessment of multiply distorted images,","venue":null,"work_id":"42792293-1bf7-462b-bc68-13c5f91cafb8","year":2013},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:15.998379Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:03b17c251aea9186263262f5817b7564616e8b8c2766b372a96eb7c28bb96523","observation_id":"1289de6b-caf4-495d-853e-395061e281b9","resolution":{"observed_at":"2026-08-06T22:21:11.290016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.147616Z","title":"No-reference image quality assessment in the spatial domain,","venue":null,"work_id":"f4ff408d-d526-468f-9928-3a7c9e214f80","year":2012},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.054862Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:ce854312cae499589739fcef0c054a4ce23ffc562124b1520b904de801530ecd","observation_id":"4674c948-0bdc-4830-9407-34292f4d9ccb","resolution":{"observed_at":"2026-08-06T22:21:11.201374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:11.033866Z","title":"Convolutional neural networks for no-reference image quality assessment,","venue":null,"work_id":"1e58bb1d-6c5e-44ed-9a9c-ae9539ee88d5","year":2014},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.114168Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:f15873aa7fde6cbe08052fe48d765cd498ede6df81fb3deb7f0334295c36b608","observation_id":"f1cba77e-0410-43c1-8fe6-38003deacfbc","resolution":{"observed_at":"2026-08-06T22:21:11.096850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:20:16.189670Z","title":"Deep residual learning for image recognition,","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.189670Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:729fb4932809d27430237972d92099b990118143f39a29a3f8b786297fc0a42b","observation_id":"a406e5f7-6bb9-4e8c-9d65-24ebe8d7a5cf","resolution":{"observed_at":"2026-08-06T22:20:16.189670Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1409.1556","last_updated":"2015-04-10T16:25:04Z","snapshot_observed_at":"2026-07-06T03:53:32.549552Z","submitted_at":"2014-09-04T19:48:04Z","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1409.1556","snapshot_observed_at":"2026-08-06T22:20:16.258406Z","title":"Very deep convolutional networks for large-scale image recognition,","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.258406Z"},"links":{"cited_paper":"/paper/1409.1556","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:720c580b9ddcae37f599b04f3786a9c6aee5088a48ca58395eef74202fd30428","observation_id":"5087ee2a-bce1-4829-8389-1bdf5e77066c","resolution":{"observed_at":"2026-08-06T22:20:16.258406Z","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":"2026-08-06T22:21:10.938760Z","title":"Blindly assess image quality in the wild guided by a self-adaptive hyper network,","venue":null,"work_id":"69745123-1bbe-422f-b2b8-cd9775b261c1","year":2020},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.342548Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:2cba85345debdf370ffd9b9d1c531b27ffac684d8eef09e4feaaa1f96d0b6d3a","observation_id":"b0595358-d951-4883-867c-b145cf1eee1d","resolution":{"observed_at":"2026-08-06T22:21:10.981977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.08958","last_updated":"2022-04-21T03:08:48Z","snapshot_observed_at":"2026-07-06T13:01:44.644805Z","submitted_at":"2022-04-19T15:56:43Z","title":"MANIQA: Multi-dimension Attention Network for No-Reference Image Quality Assessment","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2204.08958","snapshot_observed_at":"2026-08-06T22:20:16.448182Z","title":"MANIQA: Multi-dimension Attention Network for No-Reference Im- age Quality Assessment,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.448182Z"},"links":{"cited_paper":"/paper/2204.08958","citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:7127dee0fc5846bc62a804a74fc7442eebf11604532cebf1c2798dad26078973","observation_id":"3c957b1a-7363-470c-8463-88f4d8c9bd6a","resolution":{"observed_at":"2026-08-06T22:20:16.448182Z","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":"2026-08-06T22:20:16.520266Z","title":"No-reference im- age quality assessment via transformers, relative ranking, and self- consistency,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.520266Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:9b9045c875892c58a4fed9ada509fe5d3a2520763b9202a1da6581bd987cd6e7","observation_id":"3b5ec36d-df2f-4fac-b786-d81807dc3260","resolution":{"observed_at":"2026-08-06T22:20:16.520266Z","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":"2026-08-06T22:21:10.794365Z","title":"Eva: Exploring the limits of masked visual representation learning at scale,","venue":null,"work_id":"4b12c614-7a1e-431e-a37a-6c06b19ee2e7","year":2023},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.614082Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:973d95b5a37c668dfd72fa283d64527b7252d78873a073a028413a467871858f","observation_id":"5588dd62-a974-4078-95cd-90fd47ecfa08","resolution":{"observed_at":"2026-08-06T22:21:10.855183Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.712028Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation,","venue":null,"work_id":"c8ecc19a-c2c4-4db5-ae63-217e34d5f040","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.666806Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:ddcaea177bacd7cc9a29a4a9f5a5719cd8d0ccc52d7d80a6924d88c46222df31","observation_id":"8bdcc2db-afbf-4628-9abb-810709de7c5d","resolution":{"observed_at":"2026-08-06T22:21:10.755303Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.590981Z","title":"On the accuracy of objective image and video quality models: New methodology for performance evaluation,","venue":null,"work_id":"91a75ede-cec4-4fe8-a98f-9e467ae0ea89","year":2016},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.775633Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:f8ac5d01c3e6ce0db8e30965e736cb229987f2b2d372a6e3e33763bd8ac5b42b","observation_id":"00a5387f-fca8-4103-8118-b528843d9088","resolution":{"observed_at":"2026-08-06T22:21:10.631864Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.483931Z","title":"Quality assessment of sharpened images: Challenges, methodology, and objective metrics,","venue":null,"work_id":"fbbcfc0f-ed2b-4c69-afe1-f4a9eccaf4ab","year":2017},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.881366Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:5afa7c0ebbc9a1f47f327c9a84c0f01bb6fec84c67d54c1477c1b68e4ae27442","observation_id":"87a6d084-5226-4816-97c4-143233e05c3c","resolution":{"observed_at":"2026-08-06T22:21:10.539034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.325486Z","title":"Transalnet: Towards perceptually relevant visual saliency prediction,","venue":null,"work_id":"c74ab13f-9279-4bae-813d-ad4d7d28eb31","year":2022},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T22:20:16.951097Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:9dd07e2e880effa083db02fdf0180fea6cf79f6755a8c60d3f41bdead8a62b94","observation_id":"9db500ce-1df3-4982-8204-cf0c68c65ff8","resolution":{"observed_at":"2026-08-06T22:21:10.394594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.246026Z","title":"Context-aware saliency detection,","venue":null,"work_id":"fd03b9e8-ce44-4c10-b1cf-6b89601c9c49","year":1915},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:07.644775Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:3c8379a4db879a6e53dfe72ff5a89c2a0b6709201137713ccbe7fe50e265f89a","observation_id":"da54b5a5-5381-48c1-a7c1-6f921364ab35","resolution":{"observed_at":"2026-08-06T22:21:10.274566Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.137940Z","title":"Graph-based visual saliency,","venue":null,"work_id":"a113eae7-e24b-4885-be0e-1eb409ef51b4","year":2006},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:07.718220Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:1cf37f1b411b4360464b67ecdc5d8f2ee959272de340391c6eca8a4219629c6f","observation_id":"0b622d59-4a8d-4c58-94d1-43f6a8aacdab","resolution":{"observed_at":"2026-08-06T22:21:10.187719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:10.027694Z","title":"Visual saliency based on scale-space analysis in the frequency domain,","venue":null,"work_id":"7bf7aaa9-7487-4dfe-bb97-df4294ebac69","year":2012},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:07.809877Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:a56777bc8d0b4b800125f3995cead7779eebd03579cc87922fb529d182c87b4e","observation_id":"1940789e-2659-4ece-9c5f-5e7fa5bf5f4c","resolution":{"observed_at":"2026-08-06T22:21:10.066740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.866273Z","title":"A model of saliency-based visual atten- tion for rapid scene analysis,","venue":null,"work_id":"a1d071ef-8f8a-429d-b0e1-180e5581b5cb","year":1998},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:07.914762Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:9deba4e6bf267358a850edd13fdc5a5c82666f0b7bbafa45a632179287f3397f","observation_id":"bebce8b2-5d3b-4721-acaf-e65387e5a335","resolution":{"observed_at":"2026-08-06T22:21:09.907961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:15.030580Z","title":"Learning to predict where humans look,","venue":null,"work_id":"0f896c7f-9a6f-4112-ae7c-d82cd4c53ad8","year":2009},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:07.960403Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:a9d1de27b61177c2660f2b41a03eb7044777acabe644b420dcebee2856724335","observation_id":"8a67a67d-439a-4f82-a43f-a640a0bda6c6","resolution":{"observed_at":"2026-08-06T22:21:15.109370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.710071Z","title":"Saliency esti- mation using a non-parametric low-level vision model,","venue":null,"work_id":"50124064-b66a-4100-b886-e340726c9449","year":2011},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:08.026659Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:3652f8f2407742b1af83bae21095ed60eb24aefdedf06fc3e7df7b8404d74f60","observation_id":"f03ae8d5-3b42-4110-b28a-f3d2cf73bcc2","resolution":{"observed_at":"2026-08-06T22:21:09.761006Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.607077Z","title":"Spatio-temporal saliency detection using phase spectrum of quaternion fourier transform,","venue":null,"work_id":"f811eef2-da83-493e-92c0-d8bc4a9d6b36","year":2008},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:08.114921Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:dfd55376894474052f273882582ad0865f90a089efde646f0f55347816219793","observation_id":"a37956e8-fbfe-4587-b983-76ad9feb467e","resolution":{"observed_at":"2026-08-06T22:21:09.659863Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.454527Z","title":"Saliency detection: A spectral residual approach,","venue":null,"work_id":"7c6ee782-edeb-40f1-9be9-e9b547c690c8","year":2007},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:08.183571Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:d3384a10c4019cb1ec45069c9512d94201bb4a7ac8a923690cf199ddd365d130","observation_id":"165dd0d1-3756-41fd-93f4-08abf2c95941","resolution":{"observed_at":"2026-08-06T22:21:09.515548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.298904Z","title":"Sun: A bayesian framework for saliency using natural statistics,","venue":null,"work_id":"7d3c1bd0-f069-49af-9b92-994a5191a57e","year":2008},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:08.228435Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:c4cfb7abb874592e3859144d847962ca7de5132d60dca77e27119e4e7b0dfcf4","observation_id":"b852b560-af7a-40aa-b85f-cf4dcf2740ec","resolution":{"observed_at":"2026-08-06T22:21:09.376933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T22:21:09.190176Z","title":"Visual saliency detection by spatially weighted dissimilarity,","venue":null,"work_id":"22b250a4-c615-4fd6-a97b-a8de8c30da1b","year":2011},"citing_paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T22:21:08.251956Z"},"links":{"citing_paper":"/paper/2506.21925"},"observation_digest":"sha256:b83fc001648f47d05f12b802edc4e7d8d6446b97b5dd0ac1370bf6f3d0a6af7e","observation_id":"5c5d50e4-6723-41fb-a290-e97ec374408a","resolution":{"observed_at":"2026-08-06T22:21:09.215882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.21925","last_updated":"2025-06-27T05:36:04Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T08:13:27.921790Z","submitted_at":"2025-06-27T05:36:04Z","title":"Quality Assessment and Distortion-aware Saliency Prediction for AI-Generated Omnidirectional Images"},"reference_resolution":{"displayed":80,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":14,"verified_exact":4,"verified_fuzzy":62},"total_outbound_references":80},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2506.21925."}