{"as_of":"2026-08-08T16:58:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:da561b45ce5d89aa080c6a8d2dfa0e5df2430e3115207d5676a5930826f5f3e5","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T23:41:00.648294Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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/2506.17361/citation-record","integrity":"/paper/2506.17361/integrity","json":"/paper/2506.17361/citation-record.json","paper":"/paper/2506.17361"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T23:41:01.086481Z","title":"Hyperspectralimagesuper-resolutionviadual-domain network based on hybrid convolution","venue":null,"work_id":"86239914-ff15-47a7-8e99-f4021d295f5c","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.519500Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:dccb310b25b048d8574e6b807936c0eb41ba4decad4df2031f8f41831a42bdc7","observation_id":"27b1a84c-7fad-4827-b34f-f7695eddd14a","resolution":{"observed_at":"2026-08-06T23:41:01.090054Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.076610Z","title":"Hyperspectral anomaly detection based on machine learning: An overview","venue":null,"work_id":"fc7404bc-2274-4b0b-8de9-36e9e841220b","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.523569Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:a38e88744f92179e7a779139d4a883d445ebaf4f2f0bd70a628a78dd5fbef416","observation_id":"e0d87c1c-8cdb-43d3-961e-07b834b90c87","resolution":{"observed_at":"2026-08-06T23:41:01.080196Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.066876Z","title":"Single image super-resolution based on progressive fusion of orientation-aware features","venue":null,"work_id":"bba948c1-dd99-4842-8a18-a5a50ae759c4","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.527169Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:6e273d1aabd3b9d00ff2cb9d75cab1bf84d58a324975136ffce8f301916ec1eb","observation_id":"3403b3cc-97d2-4a64-93e8-c38219d3bffe","resolution":{"observed_at":"2026-08-06T23:41:01.070449Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.056337Z","title":"Hyperspectral image super-resolution via nonlocal low-rank tensor approximation and total variation regularization","venue":null,"work_id":"63925fb2-eba9-41cb-9a69-9fe4565b08fa","year":2017},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.531347Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:9fb38b140c954ea9bde3cb4e804f76dc0c4f619a3b941eb31788ce0af0900e3f","observation_id":"d8ef3936-5637-456d-8b67-5413798f48d4","resolution":{"observed_at":"2026-08-06T23:41:01.060257Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.045909Z","title":"Single image super-resolution based on trainable feature matching attention network","venue":null,"work_id":"b9a80b16-5b9f-4aa2-8ad5-aafd43482fc8","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.535124Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:a5b562884a8594c1269009086b3420ec354f488d0eb2ed4fc660c4e71e636fc3","observation_id":"6fff84c7-0832-4033-8dee-527a1219aee5","resolution":{"observed_at":"2026-08-06T23:41:01.049341Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.035301Z","title":"Image super-resolution using deep convolutional networks","venue":null,"work_id":"fca89067-1708-44eb-b546-566296e23975","year":2015},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.538512Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:91c77d32df46ab235e6044f8bd2a8340f05e96f8e6cd1d68bd2d3435adaea6ae","observation_id":"bd56771c-3073-415e-8006-9fcd515a5558","resolution":{"observed_at":"2026-08-06T23:41:01.039051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.024414Z","title":"Enhanced deep residual networks for single image super-resolution, in: Proceedings of the IEEE conference on computer vision and pattern recognition workshops, pp","venue":null,"work_id":"18662e8b-706f-4e27-8c9b-fa912e34e8fb","year":2017},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.542092Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:6fe3cacc083d940bd5876724fb8729d5bd34bf8e15eb918a04f34934313c4fca","observation_id":"022aa0b0-6316-4597-8715-c50b3c11e9e7","resolution":{"observed_at":"2026-08-06T23:41:01.028282Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.012561Z","title":"Hyperspectralimagesuper-resolutionbasedonspatialcorrelation-regularized unmixing convolutional neural network","venue":null,"work_id":"7f9cfa8e-6f85-4b34-85a6-bebd7a931130","year":2021},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.545155Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:ed39fe8daae09c0c10a06ee9a2cc1b262382919bf440d842912c2d5a70b94e17","observation_id":"f2fd05f5-40c3-49b2-9ae5-e15370390863","resolution":{"observed_at":"2026-08-06T23:41:01.016367Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:01.002559Z","title":"Hyperspectral image spatial super-resolution via 3d full convolutional neural network","venue":null,"work_id":"8310d43e-30aa-4a61-81a6-a7c477a3088b","year":2017},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.548284Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:7d9250b3db12af7fc757e996e5ca21a1959d9015dfefd2b87c3ad27ec0ef1d74","observation_id":"98221607-18e4-4401-b2e9-bad17f382e41","resolution":{"observed_at":"2026-08-06T23:41:01.006156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.992192Z","title":"Interactformer: Interactive transformer and cnn for hyperspectral image super-resolution","venue":null,"work_id":"3816a98f-8677-4714-a524-ff3c5e434236","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.552565Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:fc4301c2a469d24f73d57d654cab9ec65ea92f9bc10b61cd4012543d06887bfe","observation_id":"821698fb-6158-4d99-bd25-92e555f43d73","resolution":{"observed_at":"2026-08-06T23:41:00.996035Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.982121Z","title":"Learning spatial-spectral prior for super-resolution of hyperspectral imagery","venue":null,"work_id":"cb6eda3e-2ed5-4ebd-bb60-5c9ea7bff270","year":2020},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.555780Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:7e54455477a88b8df35d5b712b0286233b1f2477ebf09d2a342da6c23cd385a8","observation_id":"da7e52d3-3ac7-43cc-ada2-a71d56d05937","resolution":{"observed_at":"2026-08-06T23:41:00.985535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.971496Z","title":"Hyperspectral image super-resolution via recurrent feedback embedding and spatial–spectral consistency regularization","venue":null,"work_id":"d3362368-894e-4786-99b5-6ed7c87efb3b","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.559409Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:105eb7942e5e1b5be281a6d8c0f457b727670493c4d34225f31ac9363a950e75","observation_id":"a2d2044f-5420-47ba-8176-d8bfb7d29b53","resolution":{"observed_at":"2026-08-06T23:41:00.975234Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.960710Z","title":"Cnn-enhanced graph attention network for hyperspectral image super-resolution using non-local self-similarity","venue":null,"work_id":"5ed4fe64-07a1-4781-8d72-0a9db1c4e8ac","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.562497Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:eef90d74156f0ef728ed44199051574c56e5d64dead7549c5e48357c37b63cd1","observation_id":"0e590f9c-466c-46ab-9420-142d9b6e2f4f","resolution":{"observed_at":"2026-08-06T23:41:00.964385Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.950621Z","title":"Hyperspectral image superresolution using spectrum and feature context","venue":null,"work_id":"ab870e0e-0f2e-43b0-b0ad-dfb64df4333c","year":2020},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.565537Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:ed3cec03628dc4f29aa304c2ec18625475dfde5e2355bd414e05becdacade6d5","observation_id":"94aa78f1-ce95-45dc-8b52-7845f7d11164","resolution":{"observed_at":"2026-08-06T23:41:00.954111Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.940841Z","title":"Group shuffle and spectral-spatial fusion for hyperspectral image super-resolution","venue":null,"work_id":"182480f2-7273-4b04-8299-ae6dd09a1b90","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.568698Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:540e1a37c4fe71d5ff3f27cb3cb187fb43be160663db1fd108b89a997f2554f9","observation_id":"1b49ba5d-e7fb-465d-b9a6-3976fadf9c0d","resolution":{"observed_at":"2026-08-06T23:41:00.944109Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.930958Z","title":"Blueprint separable residual network for efficient image super-resolution, in: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp","venue":null,"work_id":"c74f3e8d-aa3b-4c0c-80d5-e8d5aa25b8ba","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.571847Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:7da9f4bd191ee96628782fd8be3f6e16db84848a3a0667e8b13d97ecfdcc4337","observation_id":"7f829f71-3b71-4a78-913f-3bc8eca3fe9c","resolution":{"observed_at":"2026-08-06T23:41:00.934361Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.920699Z","title":"Single image super-resolution based on directional variance attention network","venue":null,"work_id":"a6c17fe4-b6e6-48ba-ab1f-83b7dfcb6273","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.575189Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:f6b43c66cafa37fc411192f6800ecbc9b75359be328b48530da4ae729e236376","observation_id":"a11915ea-8ef9-42a0-ada5-8eb4948e62db","resolution":{"observed_at":"2026-08-06T23:41:00.924376Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.910889Z","title":"Hyperspectral image super-resolution using deep convolutional neural network","venue":null,"work_id":"788a49f2-baec-484c-afeb-b94520326f17","year":2017},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.578112Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:3412cb6c5f1b8788933bdaa855c6bfa81dd11ce9a6aa975a84c2dacdaa87d224","observation_id":"9153d37f-7632-415f-acc9-21ff3e2564cc","resolution":{"observed_at":"2026-08-06T23:41:00.914326Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.901571Z","title":"Hyperspectral image superresolution by transfer learning","venue":null,"work_id":"acd03322-5d17-4a6a-964e-e55eb85d3fec","year":2017},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.581072Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:76f4ecb0df13e8837c1c6c2a8d3b7d154e2c4f3f0cb4adb770479e64f990f5af","observation_id":"3dc1dec2-8737-4154-8895-b7c6890734e6","resolution":{"observed_at":"2026-08-06T23:41:00.904928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.891763Z","title":"3dfcnn: Real-time action recognition using 3d deep neural networks with raw depth information","venue":null,"work_id":"e54862ed-16eb-48db-a426-82bc3fa92dcf","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.584450Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:16d43cdf8e143d688306b8102d95e1b0a5c37e299689dd0af8f68c167e67f41a","observation_id":"d98be94d-517c-462e-81f7-35c0dbee7847","resolution":{"observed_at":"2026-08-06T23:41:00.895210Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.881860Z","title":"Mixed 2d/3d convolutional network for hyperspectral image super-resolution","venue":null,"work_id":"3bd3ea92-01ca-49ec-9f31-0973af9eba57","year":2020},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.587519Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:6222b7295a89b9c1de2bffef236c71aec671c0bf6b5dc6a5f4e14aaf456b9c0e","observation_id":"98746b9e-d044-4feb-8e5f-e193c9150566","resolution":{"observed_at":"2026-08-06T23:41:00.885217Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.872167Z","title":"Hyperspectralimagesuper-resolutionviadual-domain network based on hybrid convolution","venue":null,"work_id":"b6a7d7e9-fd10-4160-ac1b-8acec56f13a3","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.590719Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:9162dd1d2e7c34d77288cbf61908f3e22bf8a2485fbf632052f806881df9a716","observation_id":"5163595d-0b7c-4e1a-a871-01d1137d0b5d","resolution":{"observed_at":"2026-08-06T23:41:00.875717Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.862598Z","title":"Single hyperspectral image super-resolution with grouped deep recursive residual network, in: 2018 IEEE Fourth International Conference on Multimedia Big Data (BigMM), IEEE","venue":null,"work_id":"2ea86824-0cde-4760-acdd-c6fac0483577","year":2018},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.593959Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:b302282529aa50b400147178ca6718db653aba53c0ff89849d2fdde1ff22e8d9","observation_id":"35775ace-85be-4915-a3d5-b6db5f9584ee","resolution":{"observed_at":"2026-08-06T23:41:00.865990Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.853131Z","title":"A spectral grouping and attention-driven residual dense network for hyperspectral image super-resolution","venue":null,"work_id":"04e54650-aa7c-4bb2-bada-3d03d2793e8e","year":2021},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.596872Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:434d8fd2e458b17fcb7f4a77a048fcafc01c353e2c586f471ad73fa4f75b0817","observation_id":"5a0aa12b-f777-4180-aa57-89befacededd","resolution":{"observed_at":"2026-08-06T23:41:00.856444Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.843477Z","title":"Msdformer: Multiscale deformable transformer for hyperspectral image super-resolution","venue":null,"work_id":"ec17e74d-6aa8-4680-bbb8-5444a9c60219","year":null},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.599755Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:13792a1fdef54ac23f3a058d25f0ff73cee130cb22c7fcb0731619a9897795e6","observation_id":"189f91b8-7089-4cb7-bb0e-9c9b5e4e9ff3","resolution":{"observed_at":"2026-08-06T23:41:00.846959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.833609Z","title":"Msdformer: Multiscale deformable transformer for hyperspectral image super-resolution","venue":null,"work_id":"86f5841d-c7ff-4b3f-af8d-297a16a04add","year":null},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.602950Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:00c520bef56865f4af004cf8a8fa576afda27c89d2594af2bff976812cfbe78c","observation_id":"4952a268-47de-4174-950f-88bdb311172c","resolution":{"observed_at":"2026-08-06T23:41:00.837358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.824128Z","title":"Hyperspectral image super-resolution meets deep learning: A survey and perspective","venue":null,"work_id":"54e1394f-1af1-480d-99fd-995d9edc7c9c","year":null},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.606112Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:80984f95276bce89d05e0366a35c7122c5c3cf25ac07cee4c8c73c2da7520019","observation_id":"bce082ca-1a5b-4af6-894a-4236a4ff1a8b","resolution":{"observed_at":"2026-08-06T23:41:00.827880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.814766Z","title":"Remotesensingimagesuper-resolutionviamultiscaleenhancement network","venue":null,"work_id":"c8adeff9-c50d-4b65-a0f6-656c8cd4f85c","year":null},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.609493Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:91f3cf8c9f5824ddf6caf9e22b0660a66a0f5b430cee47d2ad65cafe29117c8d","observation_id":"63862582-2a9c-473e-8766-2efbfefdafc3","resolution":{"observed_at":"2026-08-06T23:41:00.818142Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.805057Z","title":"Ssir:Spatialshufflemulti-headself-attentionforsingleimagesuper-resolution","venue":null,"work_id":"e3df000f-a46c-4b58-8f98-a1104d07f380","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.612465Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:074285b90b78cc72aa878b6d50a000cdfcaf75b1dc6c32778cfd7559b08d1197","observation_id":"9ab00f5b-acb8-4ffe-9da8-1eda975ad428","resolution":{"observed_at":"2026-08-06T23:41:00.808323Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.795566Z","title":"Dense extreme inception network for edge detection","venue":null,"work_id":"83ec746a-a918-47e2-aacb-9818bc961636","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.615426Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:fbd66412e1191a943213c6df50f706ffbd9f9f88d9faa4dc581108bfa213d8ae","observation_id":"3844280c-68a9-4291-8aef-e57543c47da4","resolution":{"observed_at":"2026-08-06T23:41:00.798970Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.785298Z","title":"Focal modulation networks","venue":null,"work_id":"8914493b-8e64-44fe-844f-1edb7f1058a5","year":2022},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.618202Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:6be5b79890ea05060cd26843c07f1eed06f253fc48b9864030275a8fbc129042","observation_id":"8713156b-b872-4815-8a32-2a507c59bde4","resolution":{"observed_at":"2026-08-06T23:41:00.788893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1911.03584","last_updated":"2020-01-10T09:06:09Z","snapshot_observed_at":"2026-07-06T08:35:42.709133Z","submitted_at":"2019-11-08T23:48:38Z","title":"On the Relationship between Self-Attention and Convolutional Layers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1911.03584","snapshot_observed_at":"2026-08-06T23:41:00.620976Z","title":"On the relationship between self-attention and convolutional layers","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.620976Z"},"links":{"cited_paper":"/paper/1911.03584","citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:4c8cfef5444a259ec4065c49bbb02778250486e8203f3b05a00359efd98cc329","observation_id":"4caa92a1-c886-42a6-8d9c-3b9712fd28f2","resolution":{"observed_at":"2026-08-06T23:41:00.620976Z","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":"2026-08-06T23:41:00.774846Z","title":"Hyperspectral image classification via multiscale multiangle attention network","venue":null,"work_id":"1e7121cb-d6ca-439f-a010-2a18f7ed1fc7","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.624613Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:9ad3739bffa664ce155722c594f94e9282c1ca34ea110779235d8eb521850512","observation_id":"730e0d79-a530-47dd-b3a9-34b65c159936","resolution":{"observed_at":"2026-08-06T23:41:00.778291Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.764782Z","title":"Owrt-detr: A novel real-time transformer network for small-object detection in open-water search and rescue from uav aerial imagery","venue":null,"work_id":"ac61da30-0c86-4cb6-adfe-e498880f44d2","year":2025},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.627497Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:c976c40b258331c9c2254e9409e5ca6d96de66a7f3d1f6cb91cf20c0d9d1a296","observation_id":"b39f3af6-f28d-4de2-aea9-66c184756188","resolution":{"observed_at":"2026-08-06T23:41:00.768350Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.753201Z","title":"Spatio-spectral feature classification combining 3d-convolutionalneuralnetworkswithlongshort-termmemoryformotormovement/imagery","venue":null,"work_id":"533252bc-40ff-4f56-b279-61eca6538114","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.630328Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:f0a980c1b3a9930ba1299b8d4afbea35619be3c612200982acfe92a26fdd5803","observation_id":"4f033100-1fe1-4692-a9b7-984254eb76d0","resolution":{"observed_at":"2026-08-06T23:41:00.756960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.742093Z","title":"Combining global receptive field and spatial spectral information for single-image hyperspectral super-resolution","venue":null,"work_id":"38eae045-84d6-4110-a8c4-5bc8b9af8719","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.633245Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:d6b4b866d104cf6523bc44a3b9e90d1144b747f10168b8990fec0fd12530ac55","observation_id":"80b9a0c9-75f2-4a15-88a4-d5c0a9fa527f","resolution":{"observed_at":"2026-08-06T23:41:00.746091Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.731263Z","title":"A spatial–spectral transformer network with total variation loss for hyperspectral image denoising","venue":null,"work_id":"8e3c7d3f-616c-485f-b188-d84b2438797f","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.636306Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:c68286cd04e08d96288cd2d81597c01dd03683e842a18fee1ae36ba8bd5195ab","observation_id":"d543d10f-1439-4270-905f-89d67c548260","resolution":{"observed_at":"2026-08-06T23:41:00.734956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.721037Z","title":"Asymmetric content-aided transformer for efficient image super-resolution","venue":null,"work_id":"a5434ca1-1bcd-4d96-9fb8-bd179f5fc0ca","year":2025},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.639107Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:457a09a0e2bdbfb70f10202635c4080cd2a85a397afa8d011142a204e22d164d","observation_id":"7293a215-c235-4f4b-8111-793830d84980","resolution":{"observed_at":"2026-08-06T23:41:00.724374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.710816Z","title":"Beyondself-attention:Deformablelargekernelattentionformedicalimagesegmentation,in:ProceedingsoftheIEEE/CVF winter conference on applications of computer vision, pp","venue":null,"work_id":"2c8dce1a-2b6d-492a-bc5f-8b9187cd5a0f","year":2024},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.641925Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:38c886b2556a3159b2d485751ec8e35164ede53029e1411554bcafd163d263a6","observation_id":"ab3f50d6-1bd7-42ce-aba6-51e82ef538f5","resolution":{"observed_at":"2026-08-06T23:41:00.714394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.700017Z","title":"Patch loss: A generic multi-scale perceptual loss for single image super-resolution","venue":null,"work_id":"49bc77d6-0a76-44c9-bc86-4e771ccf2db2","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.645501Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:1da12fef70384fab4f26965144d0161f7042932255952b013fc97981050f924f","observation_id":"14ab14da-2ee8-4a98-92ae-aa4077398b20","resolution":{"observed_at":"2026-08-06T23:41:00.703777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+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":"2026-08-06T23:41:00.687713Z","title":"IEEE Transactions on Circuits and Systems for Video Technology 33, 6331–6346","venue":null,"work_id":"e9d204f9-28e5-4450-a626-e90048be7c55","year":2023},"citing_paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T23:41:00.648294Z"},"links":{"citing_paper":"/paper/2506.17361"},"observation_digest":"sha256:c273dd91aa96162ed8aed2cd68c0268432074e41e7012af47f0e383005d32487","observation_id":"ca197c88-561b-46d5-a6dd-7eb22848572f","resolution":{"observed_at":"2026-08-06T23:41:00.692668Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.17361","last_updated":"2025-06-20T10:06:48Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-06T23:34:36.512411Z","submitted_at":"2025-06-20T10:06:48Z","title":"Efficient Feedback Gate Network for Hyperspectral Image Super-Resolution"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":1,"verified_exact":0,"verified_fuzzy":40},"total_outbound_references":41},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2506.17361."}