{"as_of":"2026-08-10T16:00:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ad8e68d4d2bd1e4725d363cdef9bd3ca0bcc289a3e550431112a0a005b921638","coverage":[{"denominator":55,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":55,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:01:28.145724Z","state":"measured"},{"denominator":55,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":55,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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/2506.03740/citation-record","integrity":"/paper/2506.03740/integrity","json":"/paper/2506.03740/citation-record.json","paper":"/paper/2506.03740"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:01:30.510425Z","title":"Deep learning for image super-resolution: A survey","venue":null,"work_id":"d3073205-fc79-4b3a-8da5-c378e872b2ac","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.812848Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:186057b9cfb769d17ff54a3f3bb6d865c831ff3f3620d3155e49af0588f7315d","observation_id":"482e42d1-09b4-4000-a38a-9e47ff7246f7","resolution":{"observed_at":"2026-08-07T11:01:30.535740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.425102Z","title":"A deep journey into super-resolution: A survey","venue":null,"work_id":"423d24f0-d216-4318-a4c1-2f6f6cbeb552","year":2020},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.832714Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:fb477bdf9de5b837a454b8c87de86069f60f8c6903404ebc06ee684aaccb81df","observation_id":"a3aa76a8-63f4-4210-8913-74e02602c414","resolution":{"observed_at":"2026-08-07T11:01:30.456653Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.376865Z","title":"Super-resolution in medical imaging","venue":null,"work_id":"201816e1-f118-48be-ac81-b67374309a04","year":2009},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.868924Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:45a429f6e863c53b25bad67a1e859b1053adb7ea574c26e3849718935ae33ec6","observation_id":"e79fc829-17cd-4c44-a69a-ed31022c43fa","resolution":{"observed_at":"2026-08-07T11:01:30.395438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.305202Z","title":null,"venue":null,"work_id":"f9555337-f05e-4987-a22c-64a514122f05","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.891099Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:6d7040dea4bce82d70849c1be0c429e63035c9547164f6b1aaaf2c8f9aa430e8","observation_id":"27363b86-c438-4d47-9bf2-d806d7279385","resolution":{"observed_at":"2026-08-07T11:01:30.334695Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.186530Z","title":"Convolutional neu- ral network super resolution for face recognition in surveillance monitoring","venue":null,"work_id":"b11e40fa-2ac4-48cb-8614-a8a24ce9337d","year":2016},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.934794Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:fb0b888d93c3a68b6944ad6c6e71768ae2172690e890f9cf3b5bf22547537c3a","observation_id":"7bc3f050-cf91-47aa-8edd-bbf7595c3415","resolution":{"observed_at":"2026-08-07T11:01:30.208759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:26.956100Z","title":"Remote Sensing Image Super-Resolution via Mixed High-Order Attention Network,","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.956100Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:8fa0e88662f733f15b7ac06164af1b729d917f82b2be13f8ac0063a2c25146f2","observation_id":"44f6e5e1-b66d-488a-a0a1-8a9aba7e42d9","resolution":{"observed_at":"2026-08-07T11:01:26.956100Z","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":"2026-08-07T11:01:30.134858Z","title":"Second-order attention network for single image super-resolution","venue":null,"work_id":"4858d049-4ee1-4c05-9544-9b3d87a94330","year":2019},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.977416Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:4b2f5d6f30ac755aa3b618e9d7de865ce6dfe4c44bdd041a8c96825bfe7018b1","observation_id":"cc09216c-cfd8-4176-9418-d24fe1cc33d5","resolution":{"observed_at":"2026-08-07T11:01:30.151473Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.086876Z","title":"Image super-resolution using deep con- volutional networks","venue":null,"work_id":"a641691e-0dd0-4ad2-b066-f34d2868cb54","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.998933Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:096990d119d27b56f21506796ee6391efaa167920837d3d9c683659e9e790d15","observation_id":"593858f3-1454-4ff0-99f9-230b912c139c","resolution":{"observed_at":"2026-08-07T11:01:30.107124Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:30.039625Z","title":"Deep learning for single image super-resolution: A brief review,","venue":null,"work_id":"91acd08c-b3ca-4075-93fe-735585989278","year":2019},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.020611Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:880b998d3f4d6afe9240d6b2ccb9bbe96cba49eff2bc7d11c3f25fc1e834dd57","observation_id":"ddf5ad45-84b4-4f0d-889c-bd924398c0a4","resolution":{"observed_at":"2026-08-07T11:01:30.059562Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.934541Z","title":"Attention is all you need","venue":null,"work_id":"8d401e87-da92-4ec1-9da3-d7f53157c3ad","year":2017},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.083483Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:b3ffe3f785bea0fd4e1ea341b2ae8eb5c452f59f9e0aa67641f3c54625165c24","observation_id":"3eea72c6-01b4-4012-9966-deedc4ba9762","resolution":{"observed_at":"2026-08-07T11:01:29.952291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.898176Z","title":"Swin transformer: Hierarchical vision transformer us- ing shifted windows","venue":null,"work_id":"9b1493d4-611c-43b0-8521-a4cec51750eb","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.106400Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:56d0931e5c99a24d8fe22b988935158d8578c376a5668e06de832f05bec2883b","observation_id":"b46e8b73-0467-4988-b96c-9a9575ad4596","resolution":{"observed_at":"2026-08-07T11:01:29.915129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.09735","last_updated":"2024-08-14T06:12:36Z","snapshot_observed_at":"2026-07-06T15:04:31.778399Z","submitted_at":"2023-03-17T02:38:44Z","title":"SRFormerV2: Taking a Closer Look at Permuted Self-Attention for Image Super-Resolution","version":2},"cited_work":{"arxiv_id":"2303.09735","doi":null,"metadata_source":"pith","pith_arxiv_id":"2303.09735","snapshot_observed_at":"2026-08-07T11:01:28.327832Z","title":"SRFormerV2: Taking a Closer Look at Permuted Self-Attention for Image Super-Resolution","venue":"cs.CV","work_id":"add4c4ff-9e01-4aa4-ad54-165ceb388f1f","year":2023},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.123800Z"},"links":{"cited_paper":"/paper/2303.09735","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:59cafc1b7cf39d1d804e4f24b70e59a148fd2f628af73f356750b1ed674c6813","observation_id":"fac6519d-2ff8-4bee-baf1-5e2b0796ce24","resolution":{"observed_at":"2026-08-07T11:01:28.339558Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.846639Z","title":"Transformer for single image super-resolution","venue":null,"work_id":"1eeb02f9-161d-45e3-b37c-04a853f2084b","year":2022},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.143932Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:12a986b1c10b3c3e71b37fe8234aa384c6664fe1cd05ba273f1012a9177c17b5","observation_id":"410c13e0-f1ba-4309-ae21-4d36751e394d","resolution":{"observed_at":"2026-08-07T11:01:29.862288Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.811898Z","title":"Activating more pixels in image super resolution transformer","venue":null,"work_id":"717f0805-5097-412c-91ea-dcd0e9cf5037","year":2023},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.171942Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:b5220fb980aba4cbd21b2b8e9a4cecc442f3770762158aaebff86e6428d80f6f","observation_id":"2bd49c3f-5358-45b9-86ba-262274a6bc14","resolution":{"observed_at":"2026-08-07T11:01:29.826663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.782334Z","title":"Image super-resolution using deep convo- lutional networks","venue":null,"work_id":"78c42be4-d759-42b7-b97c-524c5e4a09b0","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.193313Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:3655d85569d8ac87ce96d0416255d59142c1a37c75dc3c8c4cc70799249caf85","observation_id":"61608381-fb70-45b3-870b-0bac56062e77","resolution":{"observed_at":"2026-08-07T11:01:29.794575Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.744821Z","title":"Accelerating the super-resolution convolutional neural network","venue":null,"work_id":"8b1fb5e6-e120-447b-a2f7-64f1afbbef8f","year":2016},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.214770Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:a3ef22ce312428d48aa90173bc98d20f0f95ae239ba036608414dd22043841b9","observation_id":"51ff8bef-66c6-4c7c-870e-81b9c5f8e399","resolution":{"observed_at":"2026-08-07T11:01:29.760689Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.715181Z","title":null,"venue":null,"work_id":"9835152f-5f8b-4b26-a461-58b8106ae98e","year":2016},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.236097Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:20a191a5f928d144d74bd22a17aced2b58252d092db84e429e497a2f1ddef809","observation_id":"6db1b789-79ef-4cd8-97c5-808ccc8a89c6","resolution":{"observed_at":"2026-08-07T11:01:29.727435Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.681697Z","title":"Enhanced deep residual networks for single image super-resolution","venue":null,"work_id":"d398b0d7-cf91-4e3a-9cd0-cd581032ef14","year":2017},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.265715Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:570336ead0c490281e6d54fadc5922b9c01fb992914b09069b420714211c6ff4","observation_id":"6e98da5d-f314-4580-b35f-df06f97d54a3","resolution":{"observed_at":"2026-08-07T11:01:29.696712Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.647417Z","title":"Residual dense network for image super- resolution, 2018","venue":null,"work_id":"d23f10a8-b2a5-4bf2-a3cc-d686dd03acf6","year":2018},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.287129Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:e8893e937c452a98370af2424de57c5e9eeb81ba49fd8ce5c5afa1660e52c9e2","observation_id":"6c4c27da-ef1f-47c3-b014-e285b2a4ad84","resolution":{"observed_at":"2026-08-07T11:01:29.662446Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.605969Z","title":"Photo-realistic single Jianfeng Wu et al.: Preprint submitted to Elsevier Page 8 of 10 Jianfeng Wu et al","venue":null,"work_id":"c8a190d7-ba23-48a0-95a5-ee9788d16764","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.308460Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:546757ea896e874fb204632aa400288b41f9af4d665f3b1156ab1ff5edd0cdf0","observation_id":"cc91a152-6772-4110-a945-06640a0fce30","resolution":{"observed_at":"2026-08-07T11:01:29.625850Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.570666Z","title":"Photo realistic single image super- resolution using a generative adversarial network","venue":null,"work_id":"416b08aa-0ebb-4bc8-a3f1-b60e62ced34b","year":2017},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.330010Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:5da4dab0f742f3af586b09c30d900c413aaff1351f1f873268e4e78b0bdd7cde","observation_id":"a43ee72c-ba6e-4558-88ad-ab3d3ac8f8ed","resolution":{"observed_at":"2026-08-07T11:01:29.585296Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.512505Z","title":"Real-esrgan: Training real-world blind super- resolution with pure synthetic data","venue":null,"work_id":"6514d35d-44e9-425e-b8ec-5b6ace231e64","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.359937Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:cf9c64606b69b08887ee4964597115f91950e402e51d8d6c9608ad8fb0348dc3","observation_id":"7e6042db-8b1b-41ae-807e-ed182fb3bc17","resolution":{"observed_at":"2026-08-07T11:01:29.539961Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1406.2661","last_updated":"2014-06-10T18:58:17Z","snapshot_observed_at":"2026-07-06T03:46:00.791740Z","submitted_at":"2014-06-10T18:58:17Z","title":"Generative Adversarial Networks","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1406.2661","snapshot_observed_at":"2026-08-07T11:01:27.381239Z","title":"Generative adversarial networks","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.381239Z"},"links":{"cited_paper":"/paper/1406.2661","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:f0ed11bb695d395c25e330cbb2c00dfffdacbad46c3a4c9d3da6d722562394d5","observation_id":"3a2c80d2-3803-4d43-8bc8-285f992faa75","resolution":{"observed_at":"2026-08-07T11:01:27.381239Z","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":"2026-08-07T11:01:29.470016Z","title":"Non-local neural networks","venue":null,"work_id":"8d18f833-2f07-453f-9056-6c564db77225","year":2018},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.402902Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:3cd98dd9e7aec9d0c36045761cb3e88a44ded54bfa78c7ca9cced4082b5532df","observation_id":"6d840ef0-4c4a-4c0e-a238-e282f7e5002e","resolution":{"observed_at":"2026-08-07T11:01:29.482275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.968756Z","title":"Second-order attention network for single image super-resolution","venue":null,"work_id":"30ad50ab-90fb-4f77-a14c-9738abad45b5","year":2019},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.423920Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:0a6f98c113be7c70972d113f590e201238bc78e90bf42d664c974a6d6e6f169b","observation_id":"bcc968c5-0a9e-43ea-82be-83b46185179c","resolution":{"observed_at":"2026-08-07T11:01:30.001599Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2012.12877","last_updated":"2021-01-15T15:52:50Z","snapshot_observed_at":"2026-08-09T03:59:14.830524Z","submitted_at":"2020-12-23T18:42:10Z","title":"Training data-efficient image transformers & distillation through attention","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2012.12877","snapshot_observed_at":"2026-08-07T11:01:27.482186Z","title":"Training ´ data-efficient image transformers & distillation through attention","venue":null,"work_id":null,"year":2012},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.482186Z"},"links":{"cited_paper":"/paper/2012.12877","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:6fa083203394b05030097156f25b2acbb70b6f755937bc889fbb54076ea8e8ab","observation_id":"47dea056-821e-4fc9-8d04-c317edad8254","resolution":{"observed_at":"2026-08-07T11:01:27.482186Z","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":"2026-08-07T11:01:29.404733Z","title":"Segmenter: Transformer for seman- tic segmentation","venue":null,"work_id":"3e132496-9997-489a-84c0-4ac413f8346b","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.503856Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:e50beb5eb60a69c0398a510ae0d178c8bac0c4295ffb3cb731b0fac1378d379a","observation_id":"e8091912-22e8-48d5-878b-c7569c2593b7","resolution":{"observed_at":"2026-08-07T11:01:29.417187Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.363650Z","title":"Segformer: Simple and efficient design for semantic segmentation with transformers","venue":null,"work_id":"26bae8c0-7657-4a99-9809-a6e5799ad7b3","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.524997Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:df762cfa78143bc1696491eec6d71900e55826d05c914cbe3909a85e7d887f2d","observation_id":"b8805aac-21d7-4411-b5da-225209a3f260","resolution":{"observed_at":"2026-08-07T11:01:29.386025Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.328074Z","title":"Pre-trained image process- ing transformer","venue":null,"work_id":"3bd5dae8-a71d-4937-88c6-555c74cd1656","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.561999Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:a4b27dceaa286c3d4b6710b5cc3a9260d774d2f4f45c4132c5ee20c64ac6f40e","observation_id":"67e5fca7-dcc7-425a-902e-c263a4b87a94","resolution":{"observed_at":"2026-08-07T11:01:29.344220Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.272602Z","title":"Vqfr: Blind face restoration with vector-quantized dictionary and parallel decoder","venue":null,"work_id":"b782714a-d326-4d5a-b50d-5be2cad24e55","year":2022},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.583394Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:f63801522b4bafca701a703e1de358a0b0f2c8e142fa4d842aabdfd450392745","observation_id":"4946a282-5131-4aad-8577-0309864e99b2","resolution":{"observed_at":"2026-08-07T11:01:29.296249Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.435371Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":"5446cb50-52d8-4c18-8ff0-b570c2a8fd9e","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.604617Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:dbfeb3add8370a3c1981895750ef036bced7e9a526c2fa925d4e759ed5961d96","observation_id":"0db52874-1ba7-404b-99ff-78771fd2d850","resolution":{"observed_at":"2026-08-07T11:01:29.448872Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.235230Z","title":"Pre-trained image processing transformer","venue":null,"work_id":"c0f26e76-6998-4945-8597-c13ffbdb5bc0","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.625514Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:a9b962575669fb8b39a41458bbf2f61b8271aea7d8db9c07d95cf444b90ce664","observation_id":"42222849-723a-4362-8b53-3be322cf27b9","resolution":{"observed_at":"2026-08-07T11:01:29.254490Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.197309Z","title":"Swin transformer: Hierarchical vision transformer using shifted windows","venue":null,"work_id":"07d9cf35-bf98-47e2-b813-c2b5698fc294","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.647861Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:70f9bb72acedaac7eb09f968e3560d7ac2db24163aebd724f8bcdd2d22213d34","observation_id":"f9c95d68-8bd9-4d1b-9c24-d5744feed925","resolution":{"observed_at":"2026-08-07T11:01:29.217387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.142004Z","title":"Vrt: A video restoration transformer, 2022","venue":null,"work_id":"888574e4-5a81-44a5-bb34-9cd47ef231da","year":2022},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.681398Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:a130a3fd59aeaff09fda496bcb30f6132694196f2eeb11dde8e8a94e38448064","observation_id":"ae5474f5-79db-4193-91a9-4696438e5d02","resolution":{"observed_at":"2026-08-07T11:01:29.170460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.095845Z","title":"On efficient transformer and image pre- training for low level vision, 2021","venue":null,"work_id":"bb4920a5-c60f-4464-a5c6-ec727678a7c1","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.702154Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:bac308f968968d131503b61524266323950fe4ef73f894ff097bb0f5686d07ec","observation_id":"178ca104-0271-4107-ab95-b8c0cbcdd986","resolution":{"observed_at":"2026-08-07T11:01:29.115290Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:29.038097Z","title":"Swinir: Image restoration using swin transformer","venue":null,"work_id":"cf811db4-eff4-46e7-ba5e-d4c0a6219033","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.723478Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:37a222a40d0243e1ec4e8ae97a663f3032d3c2df082a58b0984af700ccfc98af","observation_id":"c1360a56-37cc-4852-b37d-27980046acd0","resolution":{"observed_at":"2026-08-07T11:01:29.065565Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.967977Z","title":"Image super-resolution us- ing very deep residual channel attention networks","venue":null,"work_id":"870cd60d-f467-41f4-89b2-90efd97925af","year":2018},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.744804Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:23a562b03ceddccd60741e20136e0c1f99281373fcd2326f35369aa5021ac131","observation_id":"cab7ad46-9b79-4dbb-a8c1-10f1677885a2","resolution":{"observed_at":"2026-08-07T11:01:28.999316Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.05128","last_updated":"2024-11-12T08:24:47Z","snapshot_observed_at":"2026-07-06T18:42:26.589950Z","submitted_at":"2024-07-06T16:34:25Z","title":"SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention","version":2},"cited_work":{"arxiv_id":"2407.05128","doi":"10.48550/arxiv.2407.05128","metadata_source":"pith","pith_arxiv_id":"2407.05128","snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"SCSA: Exploring the Synergistic Effects Between Spatial and Channel Attention","venue":"cs.CV","work_id":"262116f1-20f8-45bd-810e-17ba9e29eb63","year":2024},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.766302Z"},"links":{"cited_paper":"/paper/2407.05128","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:b74a4c1493d95bc06f166285213ae2a6c6aff98192aa09ac9a28d0102dcec142","observation_id":"7acac25f-310d-45fe-8584-197ed3782ce1","resolution":{"observed_at":"2026-08-07T11:01:28.228673Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.927060Z","title":"Image super- resolution using very deep residual channel attention networks","venue":null,"work_id":"6949651f-e84f-4b4e-ac9e-d6baf0bc1a8a","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.787976Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:cf57aa7b9b1e66f636fbfef41d3af8d65ba1ea9efda8ef41044912487cf3679e","observation_id":"0936b19f-b239-4c06-819f-5fbc993fea91","resolution":{"observed_at":"2026-08-07T11:01:28.951388Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.863183Z","title":"ECA-net: Ef- ficient channel attention for deep convolutional neural networks","venue":null,"work_id":"5d5049bb-07ba-4e66-b851-bf90b6696017","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.809952Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:1e6d407eb52ef51fc3fb17e53715b485b2e27288902ae60a2d625e38faa05dc1","observation_id":"17fff20e-f3e3-4b25-a9ee-deb5d1c285ce","resolution":{"observed_at":"2026-08-07T11:01:28.888459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.814425Z","title":"chal- lenge on single image super-resolution: Methods and results","venue":null,"work_id":"53a4e8b0-d452-41ce-a645-6f801ed72c22","year":2018},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.832148Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:aa093e4723974f4c625048472149a1dd97f6e81bb7d7965c3b080a5d2f7b0dc7","observation_id":"20fbee00-8380-4c8b-ac7e-c5b5c080ba83","resolution":{"observed_at":"2026-08-07T11:01:28.829920Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.757777Z","title":"Enhanced deep residual net- works for single image super-resolution","venue":null,"work_id":"4c8cc392-4d2c-410e-bcc8-172b4131fdb4","year":2017},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.858217Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:3e5eca4740dfdcc6d03d4150480eeeda5b63fef7a05a3c641cf6522774b3e1e2","observation_id":"9a3f297d-4cfb-4d40-80ce-f41ffb33526c","resolution":{"observed_at":"2026-08-07T11:01:28.777180Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.728964Z","title":"Low-complexity single- image super-resolution based on nonnegative neighbor embedding","venue":null,"work_id":"c19bbfc7-ffad-49bf-8cb2-b8abf18e5af1","year":2012},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.885978Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:b745461ad3ed8880f53419b4194d5983c110080941d40f3598c0fdd52b55eced","observation_id":"f2a6f366-84f2-43b1-bb98-5c821e93c0c3","resolution":{"observed_at":"2026-08-07T11:01:28.743078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.685165Z","title":"On single image scale-up using sparse-representations","venue":null,"work_id":"85e228b5-48e5-4f09-a510-68c4a1a3086a","year":2012},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.907797Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:1e397e6a4c53bece9008f62093a2a510335f991f0ab7e8eef69cc8d980a6a13e","observation_id":"ef0afdbe-41d0-4f31-9019-cbd2cc1fe0d9","resolution":{"observed_at":"2026-08-07T11:01:28.702110Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.656490Z","title":"A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics","venue":null,"work_id":"ca76537b-e2fd-424f-ad3e-19b692ef3af0","year":2001},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.929688Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:afecfcb37847809841cecc4799f9ffbe7a747970e5b7a06dd01af6aa3cb5a957","observation_id":"2bb52af8-7b04-4ad4-9437-92f1f889adbc","resolution":{"observed_at":"2026-08-07T11:01:28.667804Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.629454Z","title":"Single image super-resolution from transformed self- exemplars","venue":null,"work_id":"c7f05be6-5ced-42a3-955e-d5b1b946942b","year":2015},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.951717Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:7e4b40e894693e27da658f3267f09aeda1c67175da994cf696a7853a2654af36","observation_id":"4d8d1201-e0ca-42ee-8d60-874196421b8e","resolution":{"observed_at":"2026-08-07T11:01:28.642243Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.603167Z","title":"Sketch-based manga retrieval using manga109 dataset","venue":null,"work_id":"6c68e67c-ef85-420b-8cb7-eea7a1efac28","year":2017},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:27.979132Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:9ec1e6817e5d696d4f99e8a22ab8204d4f6c6f9cf159857b76f3cf0180e1162b","observation_id":"6ed79be0-01a9-4165-bc59-6b959b134294","resolution":{"observed_at":"2026-08-07T11:01:28.614887Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.6980","last_updated":"2017-01-30T01:27:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","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":"2026-08-07T11:01:28.001251Z","title":"Adam: A method for stochastic optimization","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.001251Z"},"links":{"cited_paper":"/paper/1412.6980","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:e6a494f9441fb00fab51336cde439db90561b21b8ea53414a3f38253b6a6d7d5","observation_id":"b493e5f8-1ce1-4c07-83d6-b36111d3c093","resolution":{"observed_at":"2026-08-07T11:01:28.001251Z","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":"2026-08-07T11:01:28.581292Z","title":"Residual dense network for image super-resolution","venue":null,"work_id":"1ced30b6-0b9b-48be-b841-4f997779b8e5","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.023724Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:c8ba78292c47810a72d10ab063dca41aa08d4f785d009d4b7bc562cf23205771","observation_id":"7cd9ba3c-fd41-42b8-b811-df74659030a6","resolution":{"observed_at":"2026-08-07T11:01:28.593798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.548317Z","title":"Second-order attention network for single image super-resolution","venue":null,"work_id":"8e07a984-84f3-433d-a9f6-58f14039a49c","year":2019},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.044442Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:b24c813d857829ffc28259b86ef2122867c00c458510d9001ac89384f0b0da49","observation_id":"7c8bf50e-7e92-405d-89a0-447cc5fcc472","resolution":{"observed_at":"2026-08-07T11:01:28.566354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.520497Z","title":"Cross-scale internal graph neural network for image super-resolution","venue":null,"work_id":"3c605798-86ac-4fdb-919b-0c1b95b5d7e4","year":2020},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.067203Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:6c1141b48337fc2b6502817899a5364c064df77d000440bf221c4bbb800ff6db","observation_id":"3b20defe-8fdd-429a-b1c5-9f0a46723768","resolution":{"observed_at":"2026-08-07T11:01:28.533360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.479849Z","title":"Single image super-resolution via a holistic attention network","venue":null,"work_id":"49346c40-9343-4b8e-b1a1-f02d9d387d14","year":2020},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.100810Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:3bd50c0174c996906b161b3a1fe284a950c057678feca9e984e64312f259cf8c","observation_id":"e15225d6-c070-4025-b8f9-428c68e4630a","resolution":{"observed_at":"2026-08-07T11:01:28.504903Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-07T11:01:28.432462Z","title":"Image super- resolution with non-local sparse attention","venue":null,"work_id":"55b80163-6311-4ac1-ae7e-845c86d686e7","year":2021},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.123665Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:202ba0d0b53e3800457218dec49be0d5f2b7ee1a215caee46631ff6036b9f4b2","observation_id":"59e4a9fc-c0bd-42ce-9d40-e978cd09b4a0","resolution":{"observed_at":"2026-08-07T11:01:28.453026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10175","last_updated":"2022-03-21T17:32:08Z","snapshot_observed_at":"2026-07-06T12:20:22.502449Z","submitted_at":"2021-12-19T15:50:48Z","title":"On Efficient Transformer-Based Image Pre-training for Low-Level Vision","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2112.10175","snapshot_observed_at":"2026-08-07T11:01:28.145724Z","title":"On efficient transformer-based im- age pre-training for low-level vision","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:28.145724Z"},"links":{"cited_paper":"/paper/2112.10175","citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:ff827ad9a6827a34398f23915d19d4fa661a1c36ba62a16e76e00475e8ae8c27","observation_id":"45b86105-82d7-4e8f-811c-dc2586d7bcfc","resolution":{"observed_at":"2026-08-07T11:01:28.145724Z","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":"2026-08-07T11:01:30.261994Z","title":"In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","venue":null,"work_id":"81a10127-f7f2-49a2-a120-4d06f83584d5","year":null},"citing_paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution","version":1},"reference_index":2017,"source":"pdf_text","source_observed_at":"2026-08-07T11:01:26.912913Z"},"links":{"citing_paper":"/paper/2506.03740"},"observation_digest":"sha256:15b356472a99b2b6ac773316f3d4a298ffb887327b29fab86210f741587f677c","observation_id":"77016084-5820-4613-9e6d-badd3d9b754c","resolution":{"observed_at":"2026-08-07T11:01:30.275275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.03740","last_updated":"2025-06-04T09:12:24Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T03:59:51.516939Z","submitted_at":"2025-06-04T09:12:24Z","title":"SAAT: Synergistic Alternating Aggregation Transformer for Image Super-Resolution"},"reference_resolution":{"displayed":55,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":7,"verified_exact":1,"verified_fuzzy":46},"total_outbound_references":55},"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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2506.03740."}