{"as_of":"2026-08-08T09:32:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0b3851587727a9ac8a82d09d88e0b7db94f2a94f866055f98b7a4dceea5be041","coverage":[{"denominator":24,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":24,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:18:58.328951Z","state":"measured"},{"denominator":25,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":25,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+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":"2026-08-07T05:18:54.798241Z","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":"2026-08-07T05:18:58.800130Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"cited_work":{"arxiv_id":"2506.08299","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.08299","snapshot_observed_at":"2026-08-07T05:18:58.800130Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","venue":"cs.CV","work_id":"117affe4-a3bb-453b-b796-e4af3b81087d","year":2025},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:54.798241Z"},"links":{"cited_paper":"/paper/2506.08299","citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:b7269112b1e9bf900dbbf1e0635c4ca7bdc254a74bc515a213a9e3ee6d66f040","observation_id":"3b9350d7-c71c-4a3d-869d-f5895f8d2833","resolution":{"observed_at":"2026-08-07T05:18:58.953033Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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"}}],"links":{"evidence":"/evidence","html":"/paper/2506.08299/citation-record","integrity":"/paper/2506.08299/integrity","json":"/paper/2506.08299/citation-record.json","paper":"/paper/2506.08299"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"cited_work":{"arxiv_id":"2506.08299","doi":null,"metadata_source":"pith","pith_arxiv_id":"2506.08299","snapshot_observed_at":"2026-08-07T05:18:58.800130Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","venue":"cs.CV","work_id":"117affe4-a3bb-453b-b796-e4af3b81087d","year":2025},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:54.798241Z"},"links":{"cited_paper":"/paper/2506.08299","citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:b7269112b1e9bf900dbbf1e0635c4ca7bdc254a74bc515a213a9e3ee6d66f040","observation_id":"3b9350d7-c71c-4a3d-869d-f5895f8d2833","resolution":{"observed_at":"2026-08-07T05:18:58.953033Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"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":"2026-08-07T05:19:05.328914Z","title":null,"venue":null,"work_id":"67df5118-1d72-4578-b7d9-a858da13f5d5","year":null},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:54.926172Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:3fb6e3cd0d633af4c344c717ccbdd323cf61f5c0d49769f690ba5cba1fa16b3f","observation_id":"0d7178a2-5373-4fb8-90ac-a450adbe55de","resolution":{"observed_at":"2026-08-07T05:19:05.441955Z","resolver_source":"raw_fallback","status":"unresolved"},"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":"2026-08-07T05:19:05.018498Z","title":"Dataset Collection Protocol As shown in Fig","venue":null,"work_id":"8293f838-3d2b-482a-aa4e-0b5253a2dad9","year":2017},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.099744Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:d59669cd98138f0614343693335249c1b760b4e98ccabb9e6b9f1755aa47c815","observation_id":"0f0c23fb-6ce0-46c4-9144-616d759ce5b3","resolution":{"observed_at":"2026-08-07T05:19:05.153304Z","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":"2026-08-07T05:19:04.671020Z","title":"conv2 2”, “conv3 2","venue":null,"work_id":"cbbe7d17-0c4d-4463-b267-ea901732b07b","year":null},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.302405Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:0cd6e9f938a7742a257c8d8251a63fefdd29770e3a1765285410135ddfb9f5e6","observation_id":"22d53b54-229e-4e19-abbe-67035dab554b","resolution":{"observed_at":"2026-08-07T05:19:04.867200Z","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":"2026-08-07T05:19:04.331561Z","title":"Our pipeline provides researchers with a more convenient way to collect diverse, high-quality true real- world data samples at low cost","venue":null,"work_id":"c259961d-e819-409e-ad27-d75cc7b5c2c3","year":null},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.434973Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:1b4177a3ba7b48f28c911050c8297a9ff61c7f1bdaf6363797aa91a78d068287","observation_id":"1d8b8d2a-9591-4e11-859d-8f95446a4846","resolution":{"observed_at":"2026-08-07T05:19:04.463393Z","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":"2026-08-07T05:19:04.050120Z","title":"Automatic acetowhite lesion segmenta- tion via specular reflection removal and deep attention network,","venue":null,"work_id":"ce42beb6-59d2-4750-8f34-c449eea66806","year":2021},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.544982Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:fc216d1eefcb3b83419234cd21a2399fa4a81bc2a64cccff3b8282fabfd18152","observation_id":"43b8361a-a039-4144-a253-3169a06a2754","resolution":{"observed_at":"2026-08-07T05:19:04.190961Z","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":"2026-08-07T05:19:03.726222Z","title":"Deep learning based end-to-end specular reflection re- moval for medical endoscopic images,","venue":null,"work_id":"ead1ea35-aef2-41a4-b6c3-adc762efdfc9","year":2023},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.649650Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:9938da4af79406544aaa0113f041fcb258eb7c6fd92a4ef1274a495f599ef775","observation_id":"f8d6b179-f015-4373-b14c-ac44fc62b156","resolution":{"observed_at":"2026-08-07T05:19:03.901723Z","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":"2026-08-07T05:19:03.356315Z","title":"A generic deep architecture for sin- gle image reflection removal and image smoothing,","venue":null,"work_id":"04634929-c6ce-4e00-91de-48a2e3a725a8","year":2017},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.771598Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:83f1d9e86797c23b5fd259b48711abcd7d6f0f7de340193f929c9bc224bc49a5","observation_id":"28f4e6b4-9d60-431f-82ff-2157d39158f7","resolution":{"observed_at":"2026-08-07T05:19:03.537649Z","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":"2026-08-07T05:19:03.066134Z","title":"Single image reflection removal through cas- caded refinement,","venue":null,"work_id":"ef145e37-1acb-4628-ae58-8f329a530097","year":2020},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:55.924016Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:dc3e3bb6bf33df43b1ecc14a9038b007cc913cd97ceea9e4ca405d7934526a4c","observation_id":"5652fa63-5d13-4381-ae18-2d21d77c07c6","resolution":{"observed_at":"2026-08-07T05:19:03.199526Z","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":"2026-08-07T05:19:02.790915Z","title":"Ro- bust single image reflection removal against adversarial attacks,","venue":null,"work_id":"5d04c1b2-a5a1-4a7e-b822-c2b4c68630c2","year":2023},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.098884Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:a35e9b7fb69aa3493d648b5a9de3723772c33c633b5aa5fc92cbaaaa621726fd","observation_id":"2c718f5d-0181-4714-aba0-dae05504b32a","resolution":{"observed_at":"2026-08-07T05:19:02.922404Z","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":"2026-08-07T05:19:02.411359Z","title":"Benchmarking single-image reflec- tion removal algorithms,","venue":null,"work_id":"f0f1b5c5-4627-4d73-9f6c-bb67c5ffbd21","year":2017},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.268607Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:efd1741756eaf72f7fc5397c819a9ff3850088deb5102598c097b133136f6925","observation_id":"d3ea99b2-2f3f-4d65-810e-62883f548c30","resolution":{"observed_at":"2026-08-07T05:19:02.643370Z","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":"2026-08-07T05:19:02.058463Z","title":"Single im- age reflection separation with perceptual losses,","venue":null,"work_id":"154d8f23-bfc5-4c94-94db-45c3e0dfead8","year":2018},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.436820Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:39f48f37b593195b811e1778414d21a40eaed3c302b58834406d67f8bc8f88dd","observation_id":"4e921ac5-c8d9-4360-aa1b-1056600c5c1c","resolution":{"observed_at":"2026-08-07T05:19:02.256066Z","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":"2026-08-07T05:19:01.697816Z","title":"Polarized re- flection removal with perfect alignment in the wild,","venue":null,"work_id":"3708f7c1-7fbe-403f-9477-315f4a5da5b7","year":2020},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.551248Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:50ac7d66a5244b910d9f11f760662a518b7685d93c5c8d90df457f5347d729d1","observation_id":"55a54016-0637-4a75-8821-003f846c29e1","resolution":{"observed_at":"2026-08-07T05:19:01.843931Z","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":"2026-08-07T05:19:01.319134Z","title":"A categorized reflection removal dataset with diverse real- world scenes,","venue":null,"work_id":"69becaae-1b92-44cb-8b8e-3e48fee0c300","year":2022},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.679306Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:4e109add25d34d7a1b64efacb1bdd0f766976c739d57ed5d729e8f7332bfc1d3","observation_id":"57bec607-994e-4826-8813-eaf9ca495056","resolution":{"observed_at":"2026-08-07T05:19:01.526389Z","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":"2026-08-07T05:19:00.940948Z","title":"Revisiting single image reflection removal in the wild,","venue":null,"work_id":"398469d3-f922-4250-8543-001ec12bdb0b","year":2024},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:56.834485Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:afd0e9fd0e172e314770b73a5996741a50869495d0171525298715ae54b3372f","observation_id":"9a3e7e5a-f68e-4b18-ada3-5091b1ac56b0","resolution":{"observed_at":"2026-08-07T05:19:01.136156Z","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":"2308.00265","last_updated":"2024-11-08T15:10:11Z","snapshot_observed_at":"2026-08-07T10:09:14.247908Z","submitted_at":"2023-08-01T03:56:50Z","title":"Benchmarking Ultra-High-Definition Image Reflection Removal","version":2},"cited_work":{"arxiv_id":"2308.00265","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.00265","snapshot_observed_at":"2026-08-07T05:18:58.555103Z","title":"Benchmarking Ultra-High-Definition Image Reflection Removal","venue":"cs.CV","work_id":"f4b4fc94-f076-44ef-95c8-90fc0e780549","year":2023},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.091439Z"},"links":{"cited_paper":"/paper/2308.00265","citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:5797624e2c5ea426a0caba3d50b14540abd3a4e0fc85e2f2072dbb2aa334a1d4","observation_id":"e8e4f0cb-6dc9-4ec6-abb4-81a30915d285","resolution":{"observed_at":"2026-08-07T05:18:58.655791Z","resolver_source":"local_arxiv","status":"verified_exact"},"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":"2026-08-07T05:19:00.645822Z","title":"Robust sepa- ration of reflection from multiple images,","venue":null,"work_id":"61c4bb87-8be3-4574-943a-5c68b0c1ce4c","year":2014},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.249737Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:5c075de411949e1aa3eb591198a49128661c19e65790e9f25552aec191821218","observation_id":"3647713e-5380-4efb-9760-4ebce090c43b","resolution":{"observed_at":"2026-08-07T05:19:00.760369Z","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":"2026-08-07T05:19:00.364681Z","title":"NTIRE 2025 challenge on single image reflection removal in the wild: Datasets, methods and results,","venue":null,"work_id":"e43f09a3-bdb0-4ace-aa6c-4ab7534beac6","year":2025},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.394598Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:4e1f87b1813ab0c175ae997827695e33412e37e8829b00376d3fbd8e9706dd80","observation_id":"d3f05b65-042a-4728-b368-a3685bfed74c","resolution":{"observed_at":"2026-08-07T05:19:00.503813Z","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":"2502.08836","last_updated":"2025-02-12T22:57:06Z","snapshot_observed_at":"2026-08-07T23:28:46.965831Z","submitted_at":"2025-02-12T22:57:06Z","title":"Survey on Single-Image Reflection Removal using Deep Learning Techniques","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.08836","snapshot_observed_at":"2026-08-07T05:18:57.561946Z","title":"Survey on single-image reflection removal using deep learning techniques,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.561946Z"},"links":{"cited_paper":"/paper/2502.08836","citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:f021016db2d94e85f239de44892db187261c87c4a3894574aac494f89529ce45","observation_id":"90a3d25d-c8f3-45ea-bcb9-4a66c7e3fb13","resolution":{"observed_at":"2026-08-07T05:18:57.561946Z","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":"2026-08-07T05:19:00.088147Z","title":"Single image reflection removal exploiting misaligned training data and network enhancements,","venue":null,"work_id":"506041d8-90a0-4a03-be3d-c5f59f2b622e","year":2019},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.725318Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:703e213ed1cd6998c71d2f62c21a82847edc981cfbb61c97950236191b528bce","observation_id":"f64009b1-aa43-4039-82a8-b448a054b26d","resolution":{"observed_at":"2026-08-07T05:19:00.229657Z","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":"2026-08-07T05:18:59.800763Z","title":"Single image reflection separation via component synergy,","venue":null,"work_id":"d6473804-f357-43fe-a905-a0d8d991db82","year":2023},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:57.883145Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:59b2288c63a13771a802add56d509fee9ebb252f1196688a2a451f24875c0529","observation_id":"de5bc08b-217a-4b9e-8c89-2c5fb9f05f0e","resolution":{"observed_at":"2026-08-07T05:18:59.976656Z","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":"2026-08-07T05:18:59.487486Z","title":"Two-stage single image reflec- tion removal with reflection-aware guidance,","venue":null,"work_id":"a4e2e79c-6682-4b81-b3a5-9a47688d6573","year":2023},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:58.014746Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:65455eaba50e5135b12cda126da5063f7255e5424cc6db70fbdb0cc9d1d8f22b","observation_id":"5895b4b0-cde9-46a3-83a6-752a31ea588d","resolution":{"observed_at":"2026-08-07T05:18:59.644310Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T05:18:58.148926Z","title":"Simple baselines for image restoration,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:58.148926Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:63e7f85e0446bff170611c5fd7262b341ad5b7d33c8950694a3a0c281e45f3ca","observation_id":"cdea0058-3bb4-49f1-bf69-cd36b765af41","resolution":{"observed_at":"2026-08-07T05:18:58.148926Z","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":"2026-08-07T05:18:59.116467Z","title":"The pascal visual object classes (voc) challenge,","venue":null,"work_id":"b8fc2d73-860b-46fe-b766-ef6e26244964","year":2010},"citing_paper":{"arxiv_id":"2506.08299","last_updated":"2025-06-10T00:04:47Z","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T05:18:58.328951Z"},"links":{"citing_paper":"/paper/2506.08299"},"observation_digest":"sha256:579a11d43485634b43765853b0f217444c0ca97ad66593e0985a3ae6fd27e713","observation_id":"5084312e-3455-4259-b04c-9984728325c9","resolution":{"observed_at":"2026-08-07T05:18:59.283759Z","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":"2506.08299","last_updated":"2025-06-10T00:04:47Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-07T05:11:40.310016Z","submitted_at":"2025-06-10T00:04:47Z","title":"OpenRR-1k: A Scalable Dataset for Real-World Reflection Removal"},"reference_resolution":{"displayed":24,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":3,"verified_exact":1,"verified_fuzzy":19},"total_outbound_references":24},"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 24 of 24 outbound references and 1 inbound Pith citation observation for arXiv:2506.08299."}