{"as_of":"2026-08-10T04:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c1e3e78f8da617cf56bfd7dfbbc98d3f7eaf3509d0e10c477a0c34d7f89a43ec","coverage":[{"denominator":47,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":47,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T00:14:33.496694Z","state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":2,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":2,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T12:55:49.697340Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-13T07:12:28.060743Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":"2506.15744","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.15744","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"83044bb2-f10e-4f4e-9710-bfea0ff97cff","year":2025},"citing_paper":{"arxiv_id":"2605.12389","last_updated":"2026-05-12T16:52:02Z","snapshot_observed_at":"2026-08-02T08:29:07.957855Z","submitted_at":"2026-05-12T16:52:02Z","title":"SEMIR: Semantic Minor-Induced Representation Learning on Graphs for Visual Segmentation","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-05-13T07:10:04.177986Z"},"links":{"cited_paper":"/paper/2506.15744","citing_paper":"/paper/2605.12389"},"observation_digest":"sha256:9231e89097c546cc692b09114fa5d45884e81d5a24d4a50ca5c5bdfb84e23046","observation_id":"6fc6d3eb-4ca1-450a-9dc7-7aeabc0082d2","resolution":{"observed_at":"2026-05-13T07:12:28.063720Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.15744","snapshot_observed_at":"2026-08-01T12:55:49.697340Z","title":"arXiv preprint arXiv:2506.15744 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.22718","last_updated":"2026-07-21T16:42:48Z","snapshot_observed_at":"2026-08-03T20:32:00.886227Z","submitted_at":"2026-07-21T16:42:48Z","title":"DAMamba-UNet3D: A Parameter-Efficient Mamba State Space U-Net with Dynamic Adaptive Scan for 3D Medical Image Segmentation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-01T12:55:49.697340Z"},"links":{"cited_paper":"/paper/2506.15744","citing_paper":"/paper/2607.22718"},"observation_digest":"sha256:372e6c0af537397b986e4cc5b106bc618266018411c751a6fc0320ab9c7a0686","observation_id":"916954bd-dea9-4ccb-b030-40a55f643dae","resolution":{"observed_at":"2026-08-01T12:55:49.697340Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.15744/citation-record","integrity":"/paper/2506.15744/integrity","json":"/paper/2506.15744/citation-record.json","paper":"/paper/2506.15744"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T00:14:41.967278Z","title":"Loss odyssey in medical image segmentation","venue":null,"work_id":"e597b9ee-222f-4d35-9112-714d97feae51","year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:27.972222Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:93146fc13866633a24cfb565144ced2eb2183a145f804780492b5c987f78f6c1","observation_id":"d9ae5941-9651-4e73-894e-a6349504d986","resolution":{"observed_at":"2026-08-07T00:14:42.025952Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:41.803630Z","title":"Focal loss for dense object detection","venue":null,"work_id":"7b387093-645a-4b55-928b-dc1075d47dfc","year":2017},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.087407Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:4ea6a55418d4daf115063088fb04989634c989555518f0d9df1c73fe47a71415","observation_id":"a6a7511d-79a5-42a7-97cc-3958811ec0bb","resolution":{"observed_at":"2026-08-07T00:14:41.886101Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:41.651413Z","title":"Full-resolution residual ne tworks for semantic segmentation in street scenes","venue":null,"work_id":"ed124c37-4b14-4eaf-a058-cd54be72a612","year":2017},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.238389Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:165846a36c532ec2d4dd65371ef0f6123d0263a491b2e2995e51b2ee6d8f9a3a","observation_id":"5c7387aa-2b30-4300-aae9-cc15d351d3f9","resolution":{"observed_at":"2026-08-07T00:14:41.710382Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:41.495356Z","title":"U- net: Convolutional networks for biomedical image segmentation","venue":null,"work_id":"a14b5ec3-3b3e-46de-98e6-d856d8dccc7c","year":2015},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.403195Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:2e20ab1cf76d6441071bd277465c358f7c8a11233a5de2139965fe0c95707c5f","observation_id":"1496b53d-19a1-4acf-a524-55250f550fac","resolution":{"observed_at":"2026-08-07T00:14:41.564324Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:41.316184Z","title":"Optimizing the dice score and jaccard index for medical image segmentation: Theory and practice","venue":null,"work_id":"5c14a475-eb20-441b-b8ce-14d2cb5b6ac3","year":2019},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.496547Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:f266cd74aa2360f30edf4fbfdf43c536ecca4b982caaf41161f9f14df1652391","observation_id":"af0c5129-38b9-4eb4-93f5-a25a19a1926c","resolution":{"observed_at":"2026-08-07T00:14:41.424105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:41.158491Z","title":"Deep residual learning for ima ge recognition","venue":null,"work_id":"78888df4-d742-4303-ac85-d6fa442e9c6b","year":2016},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.671626Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:a29e935b16fb52d0668d9f52a82421fe0cb32f3e6fb6b960ac545e6360373b18","observation_id":"56ae1074-7883-417a-b6b7-1cc307736624","resolution":{"observed_at":"2026-08-07T00:14:41.228491Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2302.01027","last_updated":"2023-02-02T11:42:26Z","snapshot_observed_at":"2026-08-09T18:02:07.567543Z","submitted_at":"2023-02-02T11:42:26Z","title":"FCB-SwinV2 Transformer for Polyp Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2302.01027","snapshot_observed_at":"2026-08-07T00:14:28.834689Z","title":"FCB-Swin V2 Transformer for Polyp Segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:28.834689Z"},"links":{"cited_paper":"/paper/2302.01027","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:cd4d6b26ae5c25cf131825c877b7d3654a4c466813f49c6348b3e73d8c6b2103","observation_id":"1b1ea7a1-2308-420c-b7d3-64405772b03f","resolution":{"observed_at":"2026-08-07T00:14:28.834689Z","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":"2026-08-07T00:14:40.972277Z","title":"Kvasir-SEG: A Segmented Polyp Dataset,","venue":null,"work_id":"2db4a6f7-8375-438e-94ca-18846084914d","year":2019},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.000349Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:41f07f6786359d6e90ab6e12aea698210bf8fe1798e3d458d42a593ad1cb7a45","observation_id":"eb397ce6-fb6d-41a8-a15a-111cc1ded351","resolution":{"observed_at":"2026-08-07T00:14:41.056735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:40.797695Z","title":"WM-DOVA maps for accurate polyp highlighting in colonoscopy: Validat ion vs. saliency maps from physicians,","venue":null,"work_id":"2d3f491c-78d6-4005-9319-250795769302","year":2015},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.140536Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:4a66752c01d4cdc7240729a4ec3ba7f0e2591b504278d6e7eac72236a9d50526","observation_id":"6281d25d-1672-4f55-a482-42829667c079","resolution":{"observed_at":"2026-08-07T00:14:40.877984Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.03368","last_updated":"2019-03-29T17:36:27Z","snapshot_observed_at":"2026-08-07T00:39:52.073704Z","submitted_at":"2019-02-09T04:18:10Z","title":"Skin Lesion Analysis Toward Melanoma Detection 2018: A Challenge Hosted by the International Skin Imaging Collaboration (ISIC)","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1902.03368","snapshot_observed_at":"2026-08-07T00:14:29.335647Z","title":"Skin lesion analysis toward melanoma detection 2018: A challenge hosted by the international skin imaging collaboration (isic)","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.335647Z"},"links":{"cited_paper":"/paper/1902.03368","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:6eb7cb4c9894f83d19977f1734eb85d196cc31a2a7e48901daaba6031292e4f7","observation_id":"d46be422-b5fc-4780-8221-1577df93b3cb","resolution":{"observed_at":"2026-08-07T00:14:29.335647Z","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":"2026-08-07T00:14:40.545178Z","title":"In: International Confere nce on Medical Image Computing and Computer-Assisted Intervention","venue":null,"work_id":"f068ef84-d9f4-4987-9050-6a592f3cf8c6","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.515560Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:b4b69c9924eebb1f779bf94b2e21efa14ca69807963c76a99966b275cf1dab6b","observation_id":"a466a688-84e1-4944-a3b1-d90e2475436e","resolution":{"observed_at":"2026-08-07T00:14:40.626378Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.04306","last_updated":"2021-02-08T16:10:50Z","snapshot_observed_at":"2026-08-10T02:39:10.770770Z","submitted_at":"2021-02-08T16:10:50Z","title":"TransUNet: Transformers Make Strong Encoders for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.04306","snapshot_observed_at":"2026-08-07T00:14:29.709863Z","title":"Transunet: Transformers make strong encoders for me dical image segmentation","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.709863Z"},"links":{"cited_paper":"/paper/2102.04306","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:295d4665b6a2e4edbe85f9b71051e56ec00188ba14bf1211f53ea719e77d9cbd","observation_id":"6390e74b-3277-4947-ba7a-209651f2fea2","resolution":{"observed_at":"2026-08-07T00:14:29.709863Z","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":"2026-08-07T00:14:40.387780Z","title":"Pranet: Parallel reverse at tention network for polyp segmentation","venue":null,"work_id":"a4687dbb-6b10-470e-8c9a-a70c04afc852","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:29.863676Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:5f1ccdb8e4f1bf9b2ed705e6ae2af1248e03f6cebf90aaabfdae71447acf4431","observation_id":"c948f1d5-d52f-4bee-9d04-e8da94023081","resolution":{"observed_at":"2026-08-07T00:14:40.464660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:40.245130Z","title":"Uacanet: Uncertainty augmented context attention for polyp segmentation","venue":null,"work_id":"f60374a3-6a4a-4669-95c8-fe338f833d77","year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.053483Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:2a751ed37ffd9fe8a29b631a86f470a08b30b625bf01aee1ca50fcc02b763588","observation_id":"9c297095-b9e7-45dd-97f1-0e3ec6e30b32","resolution":{"observed_at":"2026-08-07T00:14:40.307453Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:40.130069Z","title":"nnU-Net for brain tumor segmentation","venue":null,"work_id":"9df8805b-329a-4070-ad30-b2b92802ee43","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.206853Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:f1df68528bb97b66b49f2d36cb18aad164e26c03aa43024a079ffe5b6ce0e2e5","observation_id":"8243d506-0cb7-4dea-8577-c7b781e8b82c","resolution":{"observed_at":"2026-08-07T00:14:40.175537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2303.16892","last_updated":"2023-03-29T17:58:40Z","snapshot_observed_at":"2026-08-09T12:15:14.353167Z","submitted_at":"2023-03-29T17:58:40Z","title":"Multi-scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.16892","snapshot_observed_at":"2026-08-07T00:14:30.426369Z","title":"Multi- scale Hierarchical Vision Transformer with Cascaded Attention Decoding for Medical Image Segmentation","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.426369Z"},"links":{"cited_paper":"/paper/2303.16892","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:9f2d62ebd1dee461d972128dc6d15fe78513563f5458912e11a165d120a2d1a8","observation_id":"6395c656-9f84-45f4-9b6a-f91975b92073","resolution":{"observed_at":"2026-08-07T00:14:30.426369Z","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":"2026-08-07T00:14:40.003101Z","title":"Class-balanced loss based on eff ective number of samples","venue":null,"work_id":"87e210cc-ecb1-4c29-a508-c4f826621f9d","year":2019},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.569292Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:bed4c367ad533d28964233575839d5caca8f70d3c7abaabd3a55cf9170318f53","observation_id":"2a56d6bb-5f73-4ed0-838d-09363f5b6e8e","resolution":{"observed_at":"2026-08-07T00:14:40.119299Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:39.661744Z","title":"In Proceedings of the IEEE international conference on computer vision, p ages 1395–1403, 2015","venue":null,"work_id":"1d457421-01f3-487c-b126-b5d151003357","year":2015},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.766054Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:b7fea7272a79bef17b8083caac2169e3f97d493cda66a8d7cab1888b3f96325c","observation_id":"8680f1f8-1bf7-4e03-a892-0de2dc8a57a0","resolution":{"observed_at":"2026-08-07T00:14:39.834750Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:39.419956Z","title":"Universal loss reweightin g to balance lesion size inequality in 3D medical image segmentation","venue":null,"work_id":"a1696281-76fd-4594-891f-3b914e29c367","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:30.929645Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:d1747a56dbe736cdae3f1b40793fcb4112ff8e6ad3241852885aef7b75247608","observation_id":"6f1eb4fd-4f02-4750-b7a0-7494b95001e4","resolution":{"observed_at":"2026-08-07T00:14:39.532199Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:39.102086Z","title":"Learning from imbalanced data","venue":null,"work_id":"eae32dc6-5fae-488b-9be2-b23c0d9a6d1c","year":2009},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.069079Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:5383bf4b8c5ef2044f88045db3171bee82f281b0ef768ebcac62542c04ab9d34","observation_id":"bb940e68-ede0-4424-9289-593c502f2e94","resolution":{"observed_at":"2026-08-07T00:14:39.265612Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1706.05587","last_updated":"2017-12-05T18:06:21Z","snapshot_observed_at":"2026-08-07T13:44:53.690521Z","submitted_at":"2017-06-17T22:48:57Z","title":"Rethinking Atrous Convolution for Semantic Image Segmentation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.05587","snapshot_observed_at":"2026-08-07T00:14:31.175982Z","title":"Rethinking atrous convolution for semantic image segmentation","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.175982Z"},"links":{"cited_paper":"/paper/1706.05587","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:bc0bf64eaee2f087d99aced4cf717f55555eded987eb12d61d4b8368788c1eec","observation_id":"8d65a0f7-194d-4a19-9bc9-d22bad32d194","resolution":{"observed_at":"2026-08-07T00:14:31.175982Z","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":"2026-08-07T00:14:38.782952Z","title":"Generalised dice overlap as a deep learning loss function for highly unbalanced segmentations","venue":null,"work_id":"6002d67d-9f0a-4c8b-b919-443b8c0f5f2a","year":2017},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.244277Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:38b0308e15e5d93ed963ec197eadc0f31dadcc950bbc58d86ffe99188dfd4d23","observation_id":"089db6d0-cc4c-47ae-8f62-2b68df892e85","resolution":{"observed_at":"2026-08-07T00:14:38.925433Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:38.450153Z","title":"Tversky loss function for image segment ation using 3D fully convolutional deep networks","venue":null,"work_id":"dbefada1-8ab2-40d6-8b6b-a75f1caec5d3","year":2017},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.329232Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:32a76ec5399f017c3ea24c0b0e988c7d80f1035211d2341cb2d7696ae102f678","observation_id":"c384bde4-8b60-4532-a09d-e3c51e04f33e","resolution":{"observed_at":"2026-08-07T00:14:38.546279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:38.266262Z","title":"Combo loss: Handling input and output imbalance in multi-organ segmentation","venue":null,"work_id":"94775a21-94ce-4a7f-ac19-2db6b578e90c","year":2019},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.406895Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:8c74f47835150f52e303c973454159f48da1468971f6c5f6aba161dbf49d34bc","observation_id":"8458af71-39cd-4c32-ac7d-e72f6e1aad20","resolution":{"observed_at":"2026-08-07T00:14:38.347569Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:38.078864Z","title":"Unet++: Redesigning skip connections to exploit multiscale features in image segmentation","venue":null,"work_id":"3c3e253f-2280-4dc1-9949-e6f2c94b9b1a","year":2019},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.490296Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:a5f3e202fada4f0f8534d7a96cf1ab4b953ea148863858e93300532ca14c722d","observation_id":"d77f974b-82c1-4fa7-a3fd-03dd4757ece4","resolution":{"observed_at":"2026-08-07T00:14:38.177244Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:37.878227Z","title":"Class-wise difficulty-balanced loss for solving cl ass- imbalance","venue":null,"work_id":"cea97f38-18b4-402d-8ae7-a1813187e52b","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.576235Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:977a3defb582c647fac9a5beca84365ef7c20a21a5863876f0603b9aa3bf9676","observation_id":"a18c00ba-29dd-4d75-8f64-678ae61890ad","resolution":{"observed_at":"2026-08-07T00:14:37.967462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.06885","last_updated":"2016-05-23T03:43:00Z","snapshot_observed_at":"2026-08-07T12:44:00.483963Z","submitted_at":"2016-05-23T03:43:00Z","title":"Bridging Category-level and Instance-level Semantic Image Segmentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.06885","snapshot_observed_at":"2026-08-07T00:14:31.642486Z","title":"Bridging category-level and instance-level semantic image segmentation","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.642486Z"},"links":{"cited_paper":"/paper/1605.06885","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:4d6927fbc269d8fbca6f778947f799004505f243e5494d1b1b340aa832a22b32","observation_id":"931040d1-4958-45fe-896a-ce60390c46e9","resolution":{"observed_at":"2026-08-07T00:14:31.642486Z","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":"2026-08-07T00:14:37.523717Z","title":"Learning deep representation f or imbalanced classification","venue":null,"work_id":"282b8bdf-894a-4859-ae3b-c745f3e43e39","year":2016},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.727812Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:5440684caa45626c93c0ac768143e1919583c156e35fe574d784297d7c7cd220","observation_id":"cd85ef2b-7a92-4e76-a729-128399550140","resolution":{"observed_at":"2026-08-07T00:14:37.665671Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:37.331482Z","title":"Automated volumetric assessment w ith artificial neural networks might enable a more accu rate assessment of disease burden in patients with multi ple sclerosis","venue":null,"work_id":"443e25e9-f651-4ca2-9365-0069a7c4ffca","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.815258Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:c10826165421d37c6bbd395ed36fbacc6d74817b2d69ffab69c37e47dd2702e4","observation_id":"018d1e52-81fe-49fd-b0c2-6111d940ebd3","resolution":{"observed_at":"2026-08-07T00:14:37.449977Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1809.04430","last_updated":"2021-01-13T17:43:14Z","snapshot_observed_at":"2026-08-07T17:36:34.529110Z","submitted_at":"2018-09-12T13:42:38Z","title":"Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1809.04430","snapshot_observed_at":"2026-08-07T00:14:31.925703Z","title":"Deep learning to achieve clinicall y applicable segmentation of head and neck anatomy fo r radiotherapy","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:31.925703Z"},"links":{"cited_paper":"/paper/1809.04430","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:61682ee63993281ea5aefec9a742a0e3ddec21561c640152a2eaf64522da0f8a","observation_id":"d0ea242a-18a0-4d9d-a1b8-53224438c14d","resolution":{"observed_at":"2026-08-07T00:14:31.925703Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2104.05642","last_updated":"2023-12-06T16:00:22Z","snapshot_observed_at":"2026-07-06T10:58:47.968149Z","submitted_at":"2021-04-12T17:03:42Z","title":"Common Limitations of Image Processing Metrics: A Picture Story","version":8},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2104.05642","snapshot_observed_at":"2026-08-07T00:14:32.006982Z","title":"Common limitations of image processing metrics: A picture story","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.006982Z"},"links":{"cited_paper":"/paper/2104.05642","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:8f761f1b867c5e5dfd5441a1ec07ac41423e0ed3362d460fa9166c49255eec78","observation_id":"2c223048-3fd6-4bc9-9163-fa15c923bd06","resolution":{"observed_at":"2026-08-07T00:14:32.006982Z","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":"2026-08-07T00:14:37.054972Z","title":"V-net: Fully convolutional neural networks for vol umetric medical image segmentation","venue":null,"work_id":"ea3315f3-1ee6-4386-a9d2-f34c7a760164","year":2016},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.104041Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:e9115c341baa826720bd6480e61f0e66aacdae62730153cef606d8d24bbbdf67","observation_id":"92c3758c-d7a2-4d5e-9c37-0d4682a4a534","resolution":{"observed_at":"2026-08-07T00:14:37.199651Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19751","last_updated":"2024-09-29T16:02:32Z","snapshot_observed_at":"2026-08-07T21:12:08.718799Z","submitted_at":"2024-09-29T16:02:32Z","title":"Balancing the Scales: A Comprehensive Study on Tackling Class Imbalance in Binary Classification","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.19751","snapshot_observed_at":"2026-08-07T00:14:32.187326Z","title":"Balancing the Scales: A Comprehensive Study on Tackling Class Imbalance in Binary Classification","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.187326Z"},"links":{"cited_paper":"/paper/2409.19751","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:1fc7f195d93419fe7fd9269e62641a89653127273a0b17f43ef1e9c7c14b3718","observation_id":"0a6c90a8-3e1b-4852-b941-e50da12fbb27","resolution":{"observed_at":"2026-08-07T00:14:32.187326Z","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":"2026-08-07T00:14:36.635254Z","title":"SMOTE: synthetic minority over ‐ sampling technique","venue":null,"work_id":"0ef64298-ad08-4072-8564-ebf389a1f3d3","year":2002},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.290208Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:aebca9c76628c38c0669f14694d634eb24f801448d68c8379643e1d33f5a99ee","observation_id":"4474f669-2546-42eb-bfe8-c370fbfcf1c4","resolution":{"observed_at":"2026-08-07T00:14:36.882163Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.03064","last_updated":"2021-01-08T15:30:29Z","snapshot_observed_at":"2026-08-06T20:01:49.861435Z","submitted_at":"2021-01-08T15:30:29Z","title":"One-Class Classification: A Survey","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2101.03064","snapshot_observed_at":"2026-08-07T00:14:32.376298Z","title":"One- class classification: A survey","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.376298Z"},"links":{"cited_paper":"/paper/2101.03064","citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:6329de1dd6fe3a211af0c8f53cbddf03b8379e0492266791ba3eb0bd4bcff59c","observation_id":"6607ecb8-1c16-42fa-a3d1-ad4ff4c85153","resolution":{"observed_at":"2026-08-07T00:14:32.376298Z","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":"2026-08-07T00:14:36.321308Z","title":"Handling imbalanced medical image data: A deep-learning-based one-class classification approach","venue":null,"work_id":"7e37ed6c-8058-4815-9a2f-0c1593b8b3e9","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.471511Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:21d0db379481cc9571ae9b93763afaa3a7b86efc40fd1d8cee3ad31e00bc9318","observation_id":"da0c0119-3f6c-4b38-9385-099ff4ca0050","resolution":{"observed_at":"2026-08-07T00:14:36.472919Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.948472Z","title":"Handling imbalanced medica l datasets: review of a decade of research","venue":null,"work_id":"2bf31729-b1ee-47f5-8df0-1bcc67852ab3","year":2024},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.597503Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:06a769ab2b1ec4e133c29e314392b641781152bd767140c776c9c86a36440007","observation_id":"af84c281-19c3-49d5-ad8a-74b9a86393f4","resolution":{"observed_at":"2026-08-07T00:14:36.107375Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.666271Z","title":"3D segmentation with exponent ial logarithmic loss for highly unbalanced object sizes","venue":null,"work_id":"69071f58-c4a8-46a1-8a97-9a158819d902","year":2018},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.694134Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:d422a4368fc50c1718ca4d1ccac2bedbb239d77f877f452475cdd4f5a97cff96","observation_id":"22b2a2e8-028d-4948-a9ce-2fe4b2401732","resolution":{"observed_at":"2026-08-07T00:14:35.755275Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.506214Z","title":"Focal dice loss and image dilation for brain tumor segmentation","venue":null,"work_id":"3d055bae-b17d-405c-a162-71fcdf677398","year":2018},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.782165Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:9565d471010fb6fd1c4b4c14908826ec90759fa31264216cb0526bc3a40f605a","observation_id":"9ce81980-5c22-428e-8f21-d11bc6f659a3","resolution":{"observed_at":"2026-08-07T00:14:35.576539Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.301800Z","title":"Focal dice loss-based V-Net for liver segments classification","venue":null,"work_id":"72d75b2c-084f-45d4-91eb-44091dc1fe3b","year":2022},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.847919Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:205fe45a74ff5f1afac60f10ac57a8c8a1aff7e9eedad89192a381026904f131","observation_id":"6b9d2343-4b27-4008-b03b-8e86dfba72a2","resolution":{"observed_at":"2026-08-07T00:14:35.395405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.130914Z","title":"Rethinking dice loss for me dical image segmentation","venue":null,"work_id":"fff825b3-095e-4e09-94d7-6a02dc2ccbec","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:32.945121Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:110247891bc2f097a4f2d33e705ccb5b14f3ddf0a9e3cc79998d8a38c403297c","observation_id":"4af6bc5e-5928-4f42-9c54-65460b2e7730","resolution":{"observed_at":"2026-08-07T00:14:35.195214Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:35.007330Z","title":"topK dice loss for medical image segmentation","venue":null,"work_id":"c45f7c24-f627-4df6-aef6-ffb7276bf8f9","year":null},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.022077Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:0aae2115813d968dd4d29f6f92aefdfb44df6bfa1b9a779af082b29fefde275e","observation_id":"e1a49687-1afe-49d1-896b-4fbfffdb441d","resolution":{"observed_at":"2026-08-07T00:14:35.042067Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:34.509337Z","title":"In: Multimedia Modeling: 26th Internationa l Conference, MMM (2020)","venue":null,"work_id":"52ca0e65-bd3d-4094-a814-d50d81820f3f","year":2020},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.188226Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:31d5d5e3ba28cb7542b6654b590fa79e1e663bd71c9529f78754e939f4bb3176","observation_id":"14068624-3639-4da3-99b3-113f8334f90e","resolution":{"observed_at":"2026-08-07T00:14:34.650537Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:34.285377Z","title":"Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?","venue":null,"work_id":"d9c56ac4-1931-4c2e-af6b-1c5d6e864370","year":2018},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.272649Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:e4a8b0321c11dcdf4293a68df820c566780ae5fbc10fa4ef32bb325d3eb2c14a","observation_id":"fd9bd21a-6d59-436d-9477-eedfc47966e3","resolution":{"observed_at":"2026-08-07T00:14:34.393783Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:34.012327Z","title":"MSSEG-2 challenge proceedings: Multiple sclerosis new lesions segment ation challenge using a data management and processing infrastructure","venue":null,"work_id":"9a23cfb4-f7db-44d0-a048-35f6019d4621","year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.404174Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:f4e0365c6253d07ea2fa87dc5a7de2191f7f5abdefb7c8c057189a0e3676388a","observation_id":"2317907c-c806-4179-af16-9cda073f8be4","resolution":{"observed_at":"2026-08-07T00:14:34.159507Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:33.744832Z","title":"Double encoder-decoder networks for gastrointestinal polyp segmentation","venue":null,"work_id":"70c13174-bf37-4902-ac64-7e195082f0af","year":2021},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.496694Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:1a5717a6936fb4ba9f581a3c3e220d33b23e4918914ecf845b4b64de275c3729","observation_id":"03adfeac-ff17-4208-a909-b39c135ade8c","resolution":{"observed_at":"2026-08-07T00:14:33.823345Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-07T00:14:34.844044Z","title":"Glasgow, UK, November 25-28, 2024","venue":null,"work_id":"c383133e-5051-4b72-a556-51b028c77626","year":2024},"citing_paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T00:14:33.093676Z"},"links":{"citing_paper":"/paper/2506.15744"},"observation_digest":"sha256:c4b6c3203ff8f02742ffbabffc4e2cbb8ad56c2790c26365485e04bf28440f9c","observation_id":"6dfc349e-1209-4857-bd6d-21bd8b9c0213","resolution":{"observed_at":"2026-08-07T00:14:34.916707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2506.15744","last_updated":"2025-06-17T23:09:41Z","latest_version":1,"primary_category":"eess.IV","snapshot_observed_at":"2026-08-07T12:44:28.506723Z","submitted_at":"2025-06-17T23:09:41Z","title":"Pixel-wise Modulated Dice Loss for Medical Image Segmentation"},"reference_resolution":{"displayed":47,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":10,"verified_exact":0,"verified_fuzzy":37},"total_outbound_references":47},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 47 of 47 outbound references and 2 inbound Pith citation observations for arXiv:2506.15744."}