{"as_of":"2026-08-21T15:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:2a0c61c2ab0ae50c4ca91546375285ae9ecbe3ffb9fc83e603606a024109fccc","coverage":[{"denominator":49,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T10:12:33.473781Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-21T06:32:19.484+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/2504.18818/citation-record","integrity":"/paper/2504.18818/integrity","json":"/paper/2504.18818/citation-record.json","paper":"/paper/2504.18818"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.907706Z","title":"Ntire 2017 challenge on single image super-resolution: Dataset and study","venue":null,"work_id":"bb1e6a6a-5691-41f8-a663-6f3b0f664148","year":2017},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.330355Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:e76f88dd38ceca268d2b8976e96f1355a50bb58e960d743454125d7af868c53d","observation_id":"5c95a080-988b-4fcd-b857-f590606dd7e1","resolution":{"observed_at":"2026-08-16T10:12:33.910629Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.899257Z","title":"Bevilacqua, A","venue":null,"work_id":"29aecd6b-5f38-426b-8edb-3f75c5a57ea0","year":2012},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.334227Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:16fdc4d777c7c399fa629c706c96fe7be80edc0b542fd621d19f72a462b6de40","observation_id":"afdc97c4-29c0-4972-ac17-e71c22988d60","resolution":{"observed_at":"2026-08-16T10:12:33.902266Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2310.10563","last_updated":"2023-10-16T16:36:54Z","snapshot_observed_at":"2026-08-16T14:51:41.189886Z","submitted_at":"2023-10-16T16:36:54Z","title":"RefConv: Re-parameterized Refocusing Convolution for Powerful ConvNets","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.10563","snapshot_observed_at":"2026-08-16T10:12:33.337514Z","title":"Refconv: Re-parameterized refocusing convolution for powerful convnets","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.337514Z"},"links":{"cited_paper":"/paper/2310.10563","citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:e8aa9fa83a82a2201f956af655b762b394a155cebe843af3ecb699fa57ab4852","observation_id":"79dccd8e-7072-4f97-8268-87c650e04ea8","resolution":{"observed_at":"2026-08-16T10:12:33.337514Z","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":"2026-08-16T10:12:33.890974Z","title":"Ciaosr: Continuous implicit attention-in- attention network for arbitrary-scale image super-resolution","venue":null,"work_id":"3b40eba9-29e2-4ee7-bc25-0e944d6890e2","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.340883Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:e62bff4a2cbbdabc015ec204218e785d849af587dd393ef72a95194a44939c3f","observation_id":"54b0bd10-f2e8-4ffa-8c92-4068aac9f3c9","resolution":{"observed_at":"2026-08-16T10:12:33.894252Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.882477Z","title":"Deep local shapes: Learning local sdf priors for detailed 3d reconstruction","venue":null,"work_id":"01e15d61-e157-4649-87cc-6bef70ce7d31","year":2020},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.344324Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:118c054e3672c236e247857221a4c9602f5a5c53e8ac069a207bfc65cc859866","observation_id":"45c87d51-e0d7-44ef-a44a-c0f0004014cb","resolution":{"observed_at":"2026-08-16T10:12:33.885465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.874149Z","title":"Cascaded local implicit transformer for arbitrary-scale super-resolution","venue":null,"work_id":"68c8d433-a1c6-4c10-87e8-e7bf9bd530df","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.347311Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:1f42d803a9f9eb7446c24fadeecd429bbd264dac8e120e0559c143fc5a5b91ba","observation_id":"fbb241e4-a0c8-4144-aa0d-b0160291707f","resolution":{"observed_at":"2026-08-16T10:12:33.877090Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.866158Z","title":"Learning continuous image representation with local implicit image function","venue":null,"work_id":"f4f76015-976a-40df-9590-d9d03a4ced59","year":2021},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.350804Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:c476ded75f85b27124854f65a2c738b25af1d95cbf86747e823b8e75027b89bf","observation_id":"53e6a0b5-e86a-43b7-9354-465e1c7dc341","resolution":{"observed_at":"2026-08-16T10:12:33.869094Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.858142Z","title":"Fast fourier convolution","venue":null,"work_id":"549db1fa-e630-4490-9977-59241771cc9b","year":2020},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.354660Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:b726fc31ba238009c4b677c2ac11f040ce128283100708797f4c89766a0b84b1","observation_id":"2609a0cb-7032-4f8c-8139-0b531d0a9568","resolution":{"observed_at":"2026-08-16T10:12:33.861197Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.848546Z","title":"Omni-kernel network for image restoration","venue":null,"work_id":"0afe372c-6cc0-4e5c-9a88-e4714ab7b678","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.357477Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:655e9a331fd7ba5da6b262a56b121eb7f10d04e0836b81d8d65f895eeb85cdf3","observation_id":"1e116491-124d-4717-b361-4ba354f4846c","resolution":{"observed_at":"2026-08-16T10:12:33.852560Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.840129Z","title":"Image super-resolution using deep convolutional networks","venue":null,"work_id":"59b4d343-c993-4e35-a9c2-a6a9a74fe20c","year":2015},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.360795Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:fb868ce2e4013d7cb94b60daafb520fee8f5b99ea7f017ed2b07734ef508efba","observation_id":"da7d3e16-1ff6-4c3d-9d72-89a4c80b1a5c","resolution":{"observed_at":"2026-08-16T10:12:33.843105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.831579Z","title":"Efficient frequency-domain image deraining with contrastive regulariza- tion","venue":null,"work_id":"ccf62938-b272-4a95-89e5-0a3eb4331744","year":null},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.363833Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:251e6db31e4731a398f292ce505b035748b4d74b41623a322fbce537c65d3e8f","observation_id":"37b90ef7-641c-42fd-8311-d6cab00a0faf","resolution":{"observed_at":"2026-08-16T10:12:33.834698Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.823275Z","title":"Interpreting super-resolution networks with local attribution maps","venue":null,"work_id":"57d1c78b-e345-426c-8b7f-aadd5ecb47c6","year":2021},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.366629Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:83c138e0b09861910473cb58497239da4a2220b166dd0abd3b16ee0eb104de9c","observation_id":"6fdb4cdd-cf45-4b44-92ad-05c4b93ecd24","resolution":{"observed_at":"2026-08-16T10:12:33.826454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.815021Z","title":"Meta-sr: A magnification-arbitrary network for super-resolution","venue":null,"work_id":"f3b055df-a175-4cc1-9628-7ee7d9a631a6","year":2019},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.369767Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:f53988c604d13d39d72f0d95f12b02c53ef805888b375981932078965c3cca41","observation_id":"69c2fd3c-5f32-4c49-8977-c3591602d718","resolution":{"observed_at":"2026-08-16T10:12:33.818086Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.805993Z","title":"Single image super-resolution from transformed self-exemplars","venue":null,"work_id":"35a8b057-6646-4400-a4ad-283fdc1d803b","year":2015},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.373045Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:bb510971fa0615c043d66c2b6f6131c56b41e4f11087f821457845a4650175de","observation_id":"247ea530-c0fd-45ea-b696-35cc713796ca","resolution":{"observed_at":"2026-08-16T10:12:33.809305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.375859Z","title":"Adaptive frequency filters as efficient global token mixers","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.375859Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:d72619d42e7d8d3ab39ff2a5853e02abed018f53ffe00b98de36a2e90c640920","observation_id":"0a1ff471-48cc-44c9-86aa-9b6011a37d07","resolution":{"observed_at":"2026-08-16T10:12:33.375859Z","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":"2026-08-16T10:12:33.792822Z","title":"Local implicit grid representations for 3d scenes","venue":null,"work_id":"dcb719aa-5ceb-4eb0-a249-580ec6998e94","year":2020},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.378603Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:58a1a9c92f9324e25bafbba49294a0fa8d949b2bf7d1bbf4f9ce11cb10973c31","observation_id":"c7728c52-5742-4f18-879a-dd32caecf0be","resolution":{"observed_at":"2026-08-16T10:12:33.796017Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.783237Z","title":"Fabnet: Frequency- aware binarized network for single image super-resolution","venue":null,"work_id":"63382cc3-1aac-4781-8015-d70a623533db","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.381324Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:632ba7d4dd842ca1cbe00ec9dceb791bafcd2e26494052214080b61465e276be","observation_id":"457feb4e-dc68-4563-8a1f-d07c304ce3e1","resolution":{"observed_at":"2026-08-16T10:12:33.786551Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-08-17T19:26:44.032537Z","submitted_at":"2014-12-22T13:54:29Z","title":"Adam: A Method for Stochastic Optimization","version":9},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.6980","snapshot_observed_at":"2026-08-16T10:12:33.384303Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.384303Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:99a1b10e5ba250cd9fcced973919adfb77100c8f9e11e2cb13ce94ce83f21cbc","observation_id":"026f5fa6-5bc3-4b05-bf17-02b1567890a6","resolution":{"observed_at":"2026-08-16T10:12:33.384303Z","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":"2026-08-16T10:12:33.774274Z","title":"Efficient frequency domain-based transformers for high-quality image deblurring","venue":null,"work_id":"76ab11af-d33d-4e81-ba8d-e62455c6d651","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.387179Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:4f95868de9b8911434bb117af25ac07071c8becba322b9f491f33d656408dd4e","observation_id":"b238bf60-6b17-444b-ba41-f002fda309ca","resolution":{"observed_at":"2026-08-16T10:12:33.777469Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.765031Z","title":"Local texture estimator for implicit representation function","venue":null,"work_id":"29c38cb3-e924-46c7-ab24-94686c622818","year":1929},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.389835Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:95665562cc810cf8588beee5e56f451109655510f428ebe56362ff2ba0614b35","observation_id":"b001aa14-59e3-45e2-8105-18f5481f3e31","resolution":{"observed_at":"2026-08-16T10:12:33.768500Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.756604Z","title":"Feature modulation transformer: Cross-refinement of global representation via high- frequency prior for image super-resolution","venue":null,"work_id":"df75ab7b-e1dd-4f63-aacc-811018552b98","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.393077Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:30affd980e97865e964684e35788010ab21bfb14913ca24202557063cd5a06a2","observation_id":"64514a6c-7c39-4735-afba-472986d50228","resolution":{"observed_at":"2026-08-16T10:12:33.759632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.746661Z","title":"Swinir: Image restoration using swin transformer","venue":null,"work_id":"254ad48a-e2ec-450e-a1e5-b33677218e2f","year":2021},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.395856Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:106f5db8116a23e07b913279fd67c227d2d0682c3bb28fd3621ca038299a1d59","observation_id":"62ebc833-1ac4-4f56-ab46-b92b41690bf0","resolution":{"observed_at":"2026-08-16T10:12:33.750333Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.737766Z","title":"Enhanced deep residual networks for single image super-resolution","venue":null,"work_id":"52975b5b-8249-4210-ac81-2ee8d1bb3ff2","year":2017},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.399527Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:be991b1c4d10d07e3bb406291670ac98e39a46b40d098d301b21d2b9a6fda243","observation_id":"dd4fa27f-45bf-47b2-a6e9-f4281d8945f8","resolution":{"observed_at":"2026-08-16T10:12:33.740724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.402368Z","title":"A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.402368Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:13dcb44a87e6c0cc3781156b7742082a34210f8a1ec555d9f855359d9762711e","observation_id":"3835ebba-047c-4f4f-b27f-280b3b04756f","resolution":{"observed_at":"2026-08-16T10:12:33.402368Z","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":"2026-08-16T10:12:33.405203Z","title":"Pytorch: An imperative style, high-performance deep learning library","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.405203Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:57728a1ab8f521cd1326274007217fed114b0acd3d5b171b38eb1867ff6e4342","observation_id":"cfac8aab-0e18-46e1-84c5-2034d04615b2","resolution":{"observed_at":"2026-08-16T10:12:33.405203Z","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":"2026-08-16T10:12:33.718760Z","title":"Digital image processing algorithms and applications","venue":null,"work_id":"03e7463a-2725-4ed0-badf-7f033800ff15","year":2000},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.407962Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:25967b210c7f747c00baa59cd349234d60a6f97776fbf85df13914b615670680","observation_id":"cf52a9f6-5eba-4179-8c79-98f0fa0adc92","resolution":{"observed_at":"2026-08-16T10:12:33.723001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.709783Z","title":"Leveraging frequency analysis for image denoising network pruning","venue":null,"work_id":"eae627aa-a31e-4dad-8365-1e6db8d1efcc","year":2025},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.410645Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:c4dbc8579ffd9839acd77a64990373318246a544516908d6802e6b3ec61a8d89","observation_id":"40027630-942a-4ef8-8b34-cc1a17ded603","resolution":{"observed_at":"2026-08-16T10:12:33.713242Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.700980Z","title":"Spectral representations for convolutional neural networks","venue":null,"work_id":"5376a873-79bb-40f5-9f88-8c6fb05084e2","year":2015},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.413333Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:aabc16cea1d1933d019aac49c024d32792ec573eaa184fe5393229a633f8128a","observation_id":"39d67985-754d-4e27-8f44-9648ba98846a","resolution":{"observed_at":"2026-08-16T10:12:33.704521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.691466Z","title":"Graf: Generative radiance fields for 3d-aware image synthesis","venue":null,"work_id":"5ea625ae-3b3e-4cc7-8653-97a0c528d9a6","year":2020},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.416429Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:36974d16a51fe4dcffa9ce84b19ec55340503ac65e2428a4e011bf5cba8f0062","observation_id":"066ffa21-2e51-41c6-9d52-e18bc8c0411c","resolution":{"observed_at":"2026-08-16T10:12:33.694930Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.682652Z","title":"Scene representation networks: Continuous 3d-structure-aware neural scene representations","venue":null,"work_id":"84b63515-123c-472e-aba4-ca0d00bb3dee","year":2019},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.419123Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:039756ff3dd5dcbb57a60a5e9b2a095d2d5ec3da4e8186b05974970526cd41b8","observation_id":"cbd64a58-95e4-476a-bc02-1d8d1c5b8027","resolution":{"observed_at":"2026-08-16T10:12:33.685785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.672394Z","title":"Ntire 2017 challenge on single image super-resolution: Methods and results","venue":null,"work_id":"76be758c-711b-4f59-b277-0b1cf8fb3c09","year":2017},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.421929Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:353f4f2c98ddf3f622dc2f617a70f99d8ab102e10161589826212758898a7980","observation_id":"aa558bf0-eaba-457b-94b6-6f188c937755","resolution":{"observed_at":"2026-08-16T10:12:33.676274Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.424642Z","title":"Attention is all you need","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.424642Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:19f3316ecdf2e33081827bf77b4bf544b771aae43be5de47b584a2774e985cd8","observation_id":"4f1424b3-b450-4bce-ac82-366d2ae577aa","resolution":{"observed_at":"2026-08-16T10:12:33.424642Z","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":"2026-08-16T10:12:33.658497Z","title":"Spatial-frequency mutual learning for face super-resolution","venue":null,"work_id":"d83faded-59b9-4559-8f6b-7b4fcdb2d849","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.427638Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:6ca1cd1599ebe3ca0f8f45b8b4c2cf3626be70ee071fc8a3c91fa3c446cbea7d","observation_id":"f60e9256-0e47-4dd0-bee2-34d708de15e7","resolution":{"observed_at":"2026-08-16T10:12:33.661491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.649084Z","title":"High-frequency component helps explain the generalization of convolutional neural networks","venue":null,"work_id":"4a0c5142-0f14-42cb-a2c3-1773aff39ead","year":2020},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.430504Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:98844908234f10eda793b00b19923f55861c16ef9d3e3740a57964cb362c12a5","observation_id":"c2c189e3-1858-49b9-92cf-6f519e492304","resolution":{"observed_at":"2026-08-16T10:12:33.653085Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.638932Z","title":"Group shuffle and spectral-spatial fusion for hyperspectral image super-resolution","venue":null,"work_id":"185c5244-d532-4f66-a2da-3b7041c4b778","year":2022},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.433314Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:936e4c777eeb5480787c0d1b5c238ffda85bbbc0f4a78732ef22275ecb1563f0","observation_id":"b6de623f-dc1c-4bd7-b7b8-6929057eca33","resolution":{"observed_at":"2026-08-16T10:12:33.642722Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.629505Z","title":"attention","venue":null,"work_id":"46db0906-7705-48da-aa3e-6c02c6c45afa","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.436138Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:e7e21b3820d3aa8c9dfa2e4f2c18143460a38593ea9737631b68adc53c74b521","observation_id":"b09b31a8-9b89-4ac9-b102-28af61f11e11","resolution":{"observed_at":"2026-08-16T10:12:33.633434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.439175Z","title":"Super-resolution neural operator","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.439175Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:ed6aa31adefb43f4046dd8b296a3f2495f97d48db4476d8775c4e83d70506315","observation_id":"bc52c5fe-0fb7-4ce4-8054-9ddcb7e400e7","resolution":{"observed_at":"2026-08-16T10:12:33.439175Z","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":"2026-08-16T10:12:33.616298Z","title":"Metalearning-based alternating minimization algorithm for nonconvex optimization","venue":null,"work_id":"0f1180dc-9765-4491-ae00-57fb09eeea7c","year":2022},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.441961Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:dd8eecdab24ceff52561bdd687be14b0992e0d93e30bf0b5ad22d8be037c7e2b","observation_id":"c7f265b2-9358-4b4c-9914-e387f20e130a","resolution":{"observed_at":"2026-08-16T10:12:33.619277Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.607264Z","title":"Blind super-resolution via meta-learning and markov chain monte carlo simulation","venue":null,"work_id":"c7c05041-9bd3-4b6a-808a-7bc4b833d597","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.444758Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:b18bfb8ef7b1797b4b4b7eba14c29161014ecb83d12d6cac5578ca21c889cca6","observation_id":"c395150a-d0c1-4108-a36f-8e8654e91593","resolution":{"observed_at":"2026-08-16T10:12:33.610443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.598262Z","title":"Residual quo- tient learning for zero-reference low-light image enhancement","venue":null,"work_id":"9ee58a55-09eb-4b71-b6e5-80a16949b916","year":2025},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.447548Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:4fb5a5048e67ff2fadb06ea0e464d5341506a82b04e5c412fe87a89d156509bf","observation_id":"d7436512-25e7-40af-ac45-1efc17a58ce6","resolution":{"observed_at":"2026-08-16T10:12:33.601950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.589412Z","title":"A dynamic kernel prior model for unsupervised blind image super-resolution","venue":null,"work_id":"1394a740-6775-49cf-8351-349fa804c87f","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.450256Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:c73a0352c9ead06e00ff280e644a7984724815cfc57dd3c146901140c5657377","observation_id":"5eeaca59-6a97-4973-9eac-ba5ce892497d","resolution":{"observed_at":"2026-08-16T10:12:33.592392Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.580050Z","title":"A fourier perspective on model robustness in computer vision","venue":null,"work_id":"27a1857a-4ee2-421b-9639-1679a0659b29","year":2019},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.453236Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:f86281aabe58f6a631d6891d7ff5dd79d287ffbc28f458dd32f14748799d61fa","observation_id":"dd3a5602-ff90-490e-a7e8-74b97b8a87f0","resolution":{"observed_at":"2026-08-16T10:12:33.583479Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.571522Z","title":"On single image scale-up using sparse-representations","venue":null,"work_id":"ff074499-8735-4bce-9a3b-6739d6c248a7","year":2010},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.456118Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:46e5c6a130831d8ca29181a449756e1bd99cec7e5196ffb64998176b4d0039c9","observation_id":"9ad77497-206a-4b03-bbd8-d33453d577b8","resolution":{"observed_at":"2026-08-16T10:12:33.574614Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.562778Z","title":"Anysr: Realizing image super-resolution as any-scale, any- resource","venue":null,"work_id":"839d620d-daf9-4770-b0e6-179394780f39","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.459382Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:6a4c7c2bdbf9bc9531d6e6cf6a48f9258a7801c4218aa4258ad07bf5903c6570","observation_id":"abcc4982-a65a-46e2-a49c-c9cb33c802ce","resolution":{"observed_at":"2026-08-16T10:12:33.565991Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.552658Z","title":"Residual dense network for image super-resolution","venue":null,"work_id":"715282cb-a819-4865-a688-ec816dd93aba","year":2018},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.462422Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:153d397581e1662fdaa8ce21b6dc9fe87d419d5888c10b47e2861bf435d1e4a7","observation_id":"8c5555a3-fd37-45cd-89bd-099cd1bce855","resolution":{"observed_at":"2026-08-16T10:12:33.555532Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.543162Z","title":"Activating more information in arbitrary-scale image super-resolution","venue":null,"work_id":"9c836ddf-3c7b-491b-ac2c-ef7eeb9d16ec","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.465265Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:e5ec73a246a94cf1b62d7091ad0806ae430addd32160fd0f3e31f7c9e827067c","observation_id":"071df5a0-1c59-4a62-93c8-627ff81b5bd3","resolution":{"observed_at":"2026-08-16T10:12:33.546295Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.534186Z","title":"Efficient mixed transformer for single image super-resolution","venue":null,"work_id":"28d9e52d-f1a0-48cf-8547-46b23b4e0bc7","year":2024},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.467944Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:f94cdb1571e257d8c5619a7aff448e8722d73c7cdfcaddbc5aae1ffc3f1e0e35","observation_id":"4eef5b66-b97e-4fb4-ab2a-beeb45b00ca4","resolution":{"observed_at":"2026-08-16T10:12:33.537451Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.525456Z","title":"Srformer: Permuted self-attention for single image super-resolution","venue":null,"work_id":"29d0f29c-28ec-40b4-8b2d-70ffa8251187","year":2023},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.471048Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:a41f987bc9f75e645f531090a37021c1f92c7a617df6c24150e6709557168fe3","observation_id":"0b33d389-841d-425f-a44e-81c1eb32ff75","resolution":{"observed_at":"2026-08-16T10:12:33.528443Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T10:12:33.514514Z","title":"Image super-resolution via efficient transformer embedding frequency decomposition with restart","venue":null,"work_id":"8af627bf-c13d-47d7-b767-25d9be3fe96b","year":2022},"citing_paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-16T10:12:33.473781Z"},"links":{"citing_paper":"/paper/2504.18818"},"observation_digest":"sha256:ff0fd1339b14378141e1aa06642f3ce65cfa86081a0e4c01461d49c77de14756","observation_id":"b48b357a-1d67-4613-b535-cf807c8cb8ff","resolution":{"observed_at":"2026-08-16T10:12:33.519548Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.18818","last_updated":"2025-04-26T06:12:49Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-18T20:45:06.439777Z","submitted_at":"2025-04-26T06:12:49Z","title":"Frequency-Integrated Transformer for Arbitrary-Scale Super-Resolution"},"reference_resolution":{"displayed":49,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":7,"verified_exact":0,"verified_fuzzy":42},"total_outbound_references":49},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-21T06:32:19.484+00:00","source":"crossref"},{"observed_at":"2026-08-21T06:32:16.066871+00:00","source":"retraction_watch"}],"thesis":"As of 21 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 0 inbound Pith citation observations for arXiv:2504.18818."}