{"as_of":"2026-08-18T21:51:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5ace5e3d80be6cf9148de1075164658a771f8c7e2a07564590424f60cfe060b5","coverage":[{"denominator":44,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":44,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T11:44:04.606086Z","state":"measured"},{"denominator":45,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":45,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T18:29:50.911450Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-08-08T18:29:51.390680Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"cited_work":{"arxiv_id":"2504.14826","doi":null,"metadata_source":"pith","pith_arxiv_id":"2504.14826","snapshot_observed_at":"2026-08-08T18:29:51.390680Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","venue":"cs.CV","work_id":"6036aa83-ad24-4dd8-8362-6001ad059536","year":2025},"citing_paper":{"arxiv_id":"2502.05673","last_updated":"2025-07-03T14:56:22Z","snapshot_observed_at":"2026-08-16T00:09:28.454533Z","submitted_at":"2025-02-08T19:37:33Z","title":"The Evolution of Dataset Distillation: Toward Scalable and Generalizable Solutions","version":3},"reference_index":196,"source":"pdf_text","source_observed_at":"2026-08-08T18:29:50.911450Z"},"links":{"cited_paper":"/paper/2504.14826","citing_paper":"/paper/2502.05673"},"observation_digest":"sha256:3e7ab8711286478254b8dc95b798f0b8d809f2b4fe1753130e8039b71c7cc930","observation_id":"f79087b9-7b69-4ed4-a35f-cd9fdfaa1e22","resolution":{"observed_at":"2026-08-08T18:29:51.394764Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2504.14826/citation-record","integrity":"/paper/2504.14826/integrity","json":"/paper/2504.14826/citation-record.json","paper":"/paper/2504.14826"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:44:05.249884Z","title":"A high-quality denoising dataset for smartphone cameras","venue":null,"work_id":"6bb9138f-b14b-421f-96c8-f48b099e5a9f","year":2018},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.449469Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:aaeb5d57ff276579b689e83b093c00c05c62dfa371963a4b3761c68026cd2643","observation_id":"74d5269c-295a-47b5-8576-c030288a89b5","resolution":{"observed_at":"2026-08-16T11:44:05.253663Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.238927Z","title":"Defocus deblur- ring using dual-pixel data","venue":null,"work_id":"0feb9713-ba4f-4f43-a7f1-67b0ecd5fd4d","year":2020},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.454141Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:23e2988f87d418fbfaaa62af192eed4795cde1072d9336075c3ba637dbd5526c","observation_id":"e12aaca7-f40f-460c-a1dc-d7cf4a12ebf0","resolution":{"observed_at":"2026-08-16T11:44:05.243068Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.221087Z","title":"Scail: Classifier weights scaling for class incremental learning","venue":null,"work_id":"7e8e74fb-a189-4ece-a0b3-997d9909f227","year":2020},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.458076Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:0f00c21997061455fd38e6d3ac9148c3bfbfc500d7ac2bdddffabe1f73b43e23","observation_id":"860dbbfa-e8d6-410c-ae4c-b5e72a33074b","resolution":{"observed_at":"2026-08-16T11:44:05.225069Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.210191Z","title":"Dataset distillation by matching training trajectories","venue":null,"work_id":"0b559e39-8189-4844-bcbb-28aca8f45b65","year":2022},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.461838Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:6b0c3a901b65f11a45f2b20516d20c1647edd6df9a2e47e4d07666cc6d0b41de","observation_id":"b7a63113-4941-4344-baf7-14fbe65796d0","resolution":{"observed_at":"2026-08-16T11:44:05.213761Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.199499Z","title":"Generalizing dataset dis- tillation via deep generative prior","venue":null,"work_id":"bf2f6836-ebf8-45ef-b984-eb995f2bf48c","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.466151Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:8287bee940d8efc952842f75bb2406f15e0c255146efb05b4eb11057fc5e6324","observation_id":"a70db344-0b96-4d10-a361-7cae056d32a4","resolution":{"observed_at":"2026-08-16T11:44:05.203121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.188091Z","title":"Pre- trained image processing transformer","venue":null,"work_id":"b5ab3819-4a77-46c2-91d0-05be99798d25","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.470011Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:55ca130da3035d7b1ef9ae3536f341fe8ef073a6c27ba18842d70fd3b0143872","observation_id":"abc0a8b5-81e0-487f-bf8e-0df333028474","resolution":{"observed_at":"2026-08-16T11:44:05.191989Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.176524Z","title":"Trainable nonlinear reac- tion diffusion for image restoration","venue":null,"work_id":"31fa5aab-09f8-4508-a255-f4dba4b6e56a","year":null},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.473932Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:53bba942a5ea8f21375b07ed7834d844be0b6f3c78eee2c016d0e364fe75c355","observation_id":"45024eab-ce55-4360-af2b-33356f4b95de","resolution":{"observed_at":"2026-08-16T11:44:05.180553Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2502.03656","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-16T11:44:04.798764Z","title":"A study in dataset distillation for image super-resolution.arXiv preprint arXiv:2502.03656, 2025","venue":null,"work_id":"55816368-9669-4a06-9584-cc382f5fad62","year":2025},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.477523Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:fef7717ff53dcd36fa9cb8787744e6a003084fa3af505993715bdbf33303e3e7","observation_id":"e199d870-472f-4555-8e0d-ff39424a236a","resolution":{"observed_at":"2026-08-16T11:44:04.804802Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.164866Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":"1d8adb0f-d5c7-46ef-a9ba-a7aadd015339","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.481171Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:5ead9f0e4140291a5c958431d921d61220c522201314bdc56a35cdd03f636dd4","observation_id":"89556172-341a-4d42-a8b6-adaeef459bb4","resolution":{"observed_at":"2026-08-16T11:44:05.168878Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.08430","last_updated":"2021-08-06T03:22:14Z","snapshot_observed_at":"2026-08-17T22:45:24.694319Z","submitted_at":"2021-07-18T12:55:11Z","title":"YOLOX: Exceeding YOLO Series in 2021","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.08430","snapshot_observed_at":"2026-08-16T11:44:04.484789Z","title":"Yolox: Exceeding yolo series in 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.484789Z"},"links":{"cited_paper":"/paper/2107.08430","citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:46d9cf78d9d647ae098c3e8f7b7fb8c20e36ed4796075eb2632d6ce96ae1caf4","observation_id":"accc4478-477f-492c-a2fa-1740c110770b","resolution":{"observed_at":"2026-08-16T11:44:04.484789Z","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":"2026-08-16T11:44:05.153572Z","title":"Deep residual learning for image recognition","venue":null,"work_id":"8c90e7f3-e92e-4a5f-85f6-2baaeb088b68","year":2016},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.488960Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:12e65984e2c8d62395d363f9f8a53ad28c31b9d630360a736c2a210b8aa566b6","observation_id":"93554d04-94a4-4ca5-acfb-d50f164c3922","resolution":{"observed_at":"2026-08-16T11:44:05.157525Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.142257Z","title":"Daformer: Improving network architectures and training strategies for domain-adaptive semantic segmentation","venue":null,"work_id":"3fc3532f-87c5-4a33-8a9a-c4004ba1cf86","year":2022},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.492744Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:a0f290124b2e84786089053fff81f6c1eee8f5faab7affbcd60604c1c5eaf435","observation_id":"cb926244-79d8-43ae-aa3f-a1934b9e51f9","resolution":{"observed_at":"2026-08-16T11:44:05.146342Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.131327Z","title":"Scope of validity of psnr in image/video quality assessment","venue":null,"work_id":"5a595718-79d8-4657-98c7-00e2324f2f0b","year":2008},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.496509Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:a5f8423fa4c37ad864b51a871256d0b6f72ebc0bcda6a94f670648a6c4a092e0","observation_id":"12a8e746-622c-4467-92bb-d287aa98dcb0","resolution":{"observed_at":"2026-08-16T11:44:05.135104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.120340Z","title":"Deblurgan: Blind motion deblur- ring using conditional adversarial networks","venue":null,"work_id":"76f3eba6-e9d7-47c7-b761-a45d26436c53","year":2018},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.500068Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:c52c2e3de70788ce165f691072c1aa4080944766c201d6486b6a78de510600bb","observation_id":"5b2196d6-076f-4c91-a527-31dcd3f35e93","resolution":{"observed_at":"2026-08-16T11:44:05.124087Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.108591Z","title":"Embedding fourier for ultra-high-definition low-light image 9 enhancement","venue":null,"work_id":"d7aeffa0-0f5e-45bc-9e25-b7388855c61e","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.503961Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:d8989dc6b569924aca60ecfeb7cbfff033789b5c2be79b59890f1bcc98407059","observation_id":"fd7e22b7-861f-4aef-9a0d-b724bf86574d","resolution":{"observed_at":"2026-08-16T11:44:05.112583Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.097176Z","title":"Swinir: Image restoration us- ing swin transformer","venue":null,"work_id":"7dc25572-27c5-4d91-859c-455b1ab8227e","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.507719Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:6c698077a564b1dcf7689d761d8e248adf766c8433ec54c18648156e445b3be8","observation_id":"702235f4-151b-43d5-bab9-964dcbfa117e","resolution":{"observed_at":"2026-08-16T11:44:05.100910Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.086123Z","title":"Low-level vi- sion and dynamic sampling for high-fidelity image restora- tion","venue":null,"work_id":"5ecae3a6-6290-4938-b833-c99206294c86","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.511208Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:69a7362a85b5e25bbb4e5d77af7c97bab44b30666bf36d0350bec5db69ca66e4","observation_id":"3e729773-0226-41ad-bb8b-31486b553e72","resolution":{"observed_at":"2026-08-16T11:44:05.089907Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1608.03983","last_updated":"2017-05-03T16:28:09Z","snapshot_observed_at":"2026-07-06T05:06:55.589962Z","submitted_at":"2016-08-13T13:46:05Z","title":"SGDR: Stochastic Gradient Descent with Warm Restarts","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1608.03983","snapshot_observed_at":"2026-08-16T11:44:04.515049Z","title":"Sgdr: Stochas- tic gradient descent with warm restarts","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.515049Z"},"links":{"cited_paper":"/paper/1608.03983","citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:2cbdfe49126ee2b66cfe2e449624aec6b3374ccd3623cdbf665353e24dcc892e","observation_id":"910a9c94-96e5-4817-b04d-82088f7617cd","resolution":{"observed_at":"2026-08-16T11:44:04.515049Z","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":"2026-08-16T11:44:05.074490Z","title":"Deep multi-scale convolutional neural network for dynamic scene deblurring","venue":null,"work_id":"fa8cf00d-0824-4b7e-8cf2-636ff459eef7","year":2017},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.519465Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:d3800ff2ff4e8de53ffff80ffcd16438ec151745aaf60bbec617ee8af2084bf6","observation_id":"cc4b484b-ced6-463d-9bc2-fb734313bad2","resolution":{"observed_at":"2026-08-16T11:44:05.078370Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.063161Z","title":"Ramit: Reciprocal atten- tion mixing transformer for lightweight image restoration","venue":null,"work_id":"8fa3ae59-2ad3-42aa-bd6d-cfa48531cd05","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.523168Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:3d0227c1e855b90f63e6ef3ff87e86f43382845256fb20b1d48fb67ab9449596","observation_id":"1ea6a1e9-20cd-487a-929a-abadc265cd08","resolution":{"observed_at":"2026-08-16T11:44:05.067103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.051247Z","title":"Dataset distillation with infinite ensembles","venue":null,"work_id":"1d3062a2-3748-48c8-bfd8-912ce84ac4e7","year":2022},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.527077Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:a8cff7feb97acca14053b4a5b8cebdb3b97a9f47a975322b8fa5910289a940c2","observation_id":"cda067d9-1330-43eb-97af-2fc8b0859ae5","resolution":{"observed_at":"2026-08-16T11:44:05.055391Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.530550Z","title":"Continual lifelong learning with neural networks: A review","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.530550Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:385cefc266704ac730ec7e81807ecccf7793c0e8a66052fa5bfebd6cb9df1de5","observation_id":"2421f077-8160-4ef7-8fe3-3cd2e45fd45c","resolution":{"observed_at":"2026-08-16T11:44:04.530550Z","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":"2026-08-16T11:44:05.032774Z","title":"Freqformer: Frequency- aware transformer for lightweight image super-resolution","venue":null,"work_id":"30cb6b89-3bdc-49c0-98f8-dbe304524e0e","year":2024},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.534260Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:d0a7e950a7c4c59a752f88b4c72a735a70f83333a0e31f30999038aa85fff2c8","observation_id":"edf0d3b0-de9f-491f-9510-5c6000d4d3a5","resolution":{"observed_at":"2026-08-16T11:44:05.036509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.021104Z","title":"Benchmarking denoising al- gorithms with real photographs","venue":null,"work_id":"aac4bb82-571d-4758-8f04-bff700fdd0d9","year":2017},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.537876Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:9576d0a5596f5414388135885ea2abf9fcb8849240916931a06e7e2d474ceeda","observation_id":"090ed699-6ffe-4d21-a2a4-a95aa98ac939","resolution":{"observed_at":"2026-08-16T11:44:05.025050Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:05.009904Z","title":"Promptir: Prompting for all-in-one image restoration","venue":null,"work_id":"56e9b301-f9a8-4c88-ad04-67e57c3de2e7","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.541399Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:7b3338ba2bfb5305cbbcb247e001e984ecf1de932d6cca414a9ee5281977cb2d","observation_id":"23cff3ef-a3d3-49b8-9736-715d4d3e60d8","resolution":{"observed_at":"2026-08-16T11:44:05.013696Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.544867Z","title":"icarl: Incremental classi- fier and representation learning","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.544867Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:3e40e60e988e3653921bb9b8c3e73f6f7fe4fc1b68c61638b38bea8b89489e00","observation_id":"fa2ce519-b84c-4a2f-b1e5-b4b8a970b413","resolution":{"observed_at":"2026-08-16T11:44:04.544867Z","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":"2026-08-16T11:44:04.990957Z","title":"Real- blur: A new dataset for realistic blur synthesis and deblur- ring","venue":null,"work_id":"d090dcd4-7816-441e-9d96-1362f95ab639","year":2020},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.548303Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:d1c7553ba7918072571df645751f419451338d4ad0fb8149c67aa4b1e28a4e9e","observation_id":"a4aff17e-7459-46f7-b92f-703bd6456c5c","resolution":{"observed_at":"2026-08-16T11:44:04.994902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.979477Z","title":"Active learning for convo- lutional neural networks: A core-set approach","venue":null,"work_id":"1dad9559-c182-4dad-9952-ee6b52fb3d3d","year":2018},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.551355Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:37f5d0884b4b079b9c8727ccf2377b2a91aa864cba928615f4f1acd256316784","observation_id":"f75af5c2-cbd4-4526-ba63-9b137f130ced","resolution":{"observed_at":"2026-08-16T11:44:04.983117Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.968580Z","title":"Active learning literature survey","venue":null,"work_id":"1768da5e-0392-4ed6-8a85-4d1b735556b6","year":2009},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.555174Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:8ba47c71a1ee8b4f5a02242e2cc19a4d8c4da5fddc879426c37ab0bf274db35c","observation_id":"ace7ee44-4996-419c-8c5c-fae7399246d1","resolution":{"observed_at":"2026-08-16T11:44:04.972535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.957315Z","title":"Active learning literature survey","venue":null,"work_id":"4c45beb7-10fa-49f1-bfe8-51c5a0390fcc","year":2010},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.558450Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:2300131ec5c846af1cb731cd28dcd9515b9b1f1687211cad6aa5ab1ad89e1770","observation_id":"65e42cfc-dc19-4916-bdcf-e7a6763e114c","resolution":{"observed_at":"2026-08-16T11:44:04.961211Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.945872Z","title":"Adaptive data se- lection strategies for efficient deep learning","venue":null,"work_id":"e6ef5fbe-d487-4116-99ae-d55d1d1cd6fa","year":2022},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.561792Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:6fe786f7f1df089efd129004a9e376d71c85bfc2313e328a2224e2dd67d21f67","observation_id":"cea9a2b2-390a-4a63-854a-2b0e89d948fd","resolution":{"observed_at":"2026-08-16T11:44:04.949727Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.934435Z","title":"Dataset distillation via optimal transport","venue":null,"work_id":"f6475c94-8d47-44ab-aaa8-7579cb2a4d6a","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.565453Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:52946eaefbe6b3df802e45eae4e943612141118a2aa4bcda672162178d2b8189","observation_id":"afc20140-eeb9-4395-aa35-a3ab418d41af","resolution":{"observed_at":"2026-08-16T11:44:04.938078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.568845Z","title":"Image quality assessment: from error visibility to structural similarity","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.568845Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:796f5acc268b092184c80d20671dbb888f8d6f26c1b9fa2a2a683c8d51ff6459","observation_id":"10159042-5ecd-4185-bd20-55a4d473a880","resolution":{"observed_at":"2026-08-16T11:44:04.568845Z","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":"2026-08-16T11:44:04.915992Z","title":"Dynamic dataset distillation with uncertainty estimation","venue":null,"work_id":"d745d600-03d3-4b81-a374-69b7b65c8378","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.572382Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:6f62e34ec1a25bc383c2f0f87d4bd2f739990f39235cd72589438d948bf6d5a9","observation_id":"430db1b1-8b17-48bb-bcfa-f09a25d2e55f","resolution":{"observed_at":"2026-08-16T11:44:04.919880Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.904562Z","title":"Deep joint rain detection and removal from a single image","venue":null,"work_id":"9371a35a-4718-4b1a-ac77-e24112105042","year":2017},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.575857Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:cfe390af0e5db4b7ab3fc781fc1c96c8c2a7ae571ec68d21011ef46a4bb42908","observation_id":"c432a543-1fca-499d-a5ab-93fd5ab61bf8","resolution":{"observed_at":"2026-08-16T11:44:04.908475Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.893272Z","title":"Im- age restoration with deep learning: A review.IEEE Transac- tions on Neural Networks and Learning Systems , 32:1967– 1985, 2020","venue":null,"work_id":"0a6b1cba-7b34-442b-a0a0-25a91137fd4a","year":1967},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.579001Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:58c2edb67629192a07f3973d6b2f575a1eadee6de83cf9d09c3452dc9dbff3da","observation_id":"dcdba48b-a1ad-46ed-920e-2fd37643e010","resolution":{"observed_at":"2026-08-16T11:44:04.897027Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.882367Z","title":"Restormer: Efficient transformer for high-resolution image restoration","venue":null,"work_id":"1cc37f0e-db30-41c5-8949-94c599aecc1f","year":2022},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.582525Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:a60dc6def59b3b9ea51cb9cfda59042d1e22680f2868bba230a17e13e2f9a6ce","observation_id":"5db1d57e-4b6b-481c-9ea7-5998f7240634","resolution":{"observed_at":"2026-08-16T11:44:04.886364Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.871134Z","title":"Density-aware single image de-raining using a multi-stream dense network","venue":null,"work_id":"51fc41ca-9046-4fba-9e10-74a2f87b7851","year":2018},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.585692Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:37974bb382a72a0e47b0a0e26b1e08612e3ecc91363562792ce8b82cbd54c3e7","observation_id":"55d618cc-4b60-4c50-b84d-bc18302edb04","resolution":{"observed_at":"2026-08-16T11:44:04.874999Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.859072Z","title":"Image de-raining using a con- ditional generative adversarial network","venue":null,"work_id":"f652b1ed-b7c6-45d5-8fe3-5d606e4c5c82","year":2018},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.589090Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:d25f3c6b75382396c8d63e7802ed5bde23e9eba933ba60fdcf170d1b135a6717","observation_id":"f00418d6-6bc8-4a4f-b7a7-c02924368bb9","resolution":{"observed_at":"2026-08-16T11:44:04.863236Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.847758Z","title":"Beyond a gaussian denoiser: Residual learn- ing of deep cnn for image denoising","venue":null,"work_id":"82a10bcd-f49e-42c3-973f-ac761ec2f72d","year":2017},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.592448Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:6f2235bd57de7fc904727cf6ff0d2a5eb80ab262114d67ca8b19b1bc3279513e","observation_id":"611c7549-6e30-439f-801d-8e036422967c","resolution":{"observed_at":"2026-08-16T11:44:04.851478Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.836464Z","title":"Im- age deraining with feature attention","venue":null,"work_id":"db40e522-bddb-48cf-b65a-27d378f8c887","year":2019},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.595919Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:7212651f6b430c2ddf141b951cbc0c918dbf8e50116a529c3af463758aff7934","observation_id":"df8877ec-9ef9-4bf2-8868-da2914848f46","resolution":{"observed_at":"2026-08-16T11:44:04.840413Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.823415Z","title":"Im- age restoration: A comprehensive review","venue":null,"work_id":"77834df5-3e24-45d3-bfc3-0f3b5b0d6414","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.599304Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:a7b5a3b182769b8b5b96a4278e44d396336b20c9af193079022e5e1d7cbedb52","observation_id":"b1794a86-c18b-42ec-9b69-acd46797a1d1","resolution":{"observed_at":"2026-08-16T11:44:04.828020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+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":"2026-08-16T11:44:04.812601Z","title":"Dataset condensation with gradi- ent matching","venue":null,"work_id":"3b6707d7-6cc1-4ae8-b26e-02db7dd57c2c","year":2021},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.602652Z"},"links":{"citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:22963c7161022bcf04e518938b171271357dc81f839d107cbfc5aeb9ae076377","observation_id":"6c8eb506-bdd2-4821-ad92-bcb0c34ab88e","resolution":{"observed_at":"2026-08-16T11:44:04.816372Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2301.04866","last_updated":"2023-01-12T08:19:46Z","snapshot_observed_at":"2026-08-16T21:16:12.646427Z","submitted_at":"2023-01-12T08:19:46Z","title":"Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation","version":1},"cited_work":{"arxiv_id":"2301.04866","doi":null,"metadata_source":"pith","pith_arxiv_id":"2301.04866","snapshot_observed_at":"2026-08-16T11:44:04.637696Z","title":"Self-Supervised Correction Learning for Semi-Supervised Biomedical Image Segmentation","venue":"cs.CV","work_id":"6fe433d0-7e88-4e4b-b779-b806b80e1e27","year":2023},"citing_paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-16T11:44:04.606086Z"},"links":{"cited_paper":"/paper/2301.04866","citing_paper":"/paper/2504.14826"},"observation_digest":"sha256:ec78412dd3c1986f803f8c5a1cc46bf694952858daa40eba482b7d1386f882fa","observation_id":"7bafb604-d1f6-45de-82df-22f1b86b25ba","resolution":{"observed_at":"2026-08-16T11:44:04.643676Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2504.14826","last_updated":"2025-04-21T03:00:18Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-17T07:18:40.990072Z","submitted_at":"2025-04-21T03:00:18Z","title":"Distribution-aware Dataset Distillation for Efficient Image Restoration"},"reference_resolution":{"displayed":44,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":5,"verified_exact":1,"verified_fuzzy":37},"total_outbound_references":44},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 18 August 2026, this Paper Citation Record lists 44 of 44 outbound references and 1 inbound Pith citation observation for arXiv:2504.14826."}