{"as_of":"2026-08-10T17:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:831ad4e834970f2768efbe8ba5138dab2a356415f06c491afe4784b563b14a55","coverage":[{"denominator":42,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":42,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T20:51:47.618470Z","state":"measured"},{"denominator":43,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":43,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-07T23:37:01.343477Z","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":"2026-08-07T23:37:01.532664Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"cited_work":{"arxiv_id":"2502.04970","doi":null,"metadata_source":"pith","pith_arxiv_id":"2502.04970","snapshot_observed_at":"2026-08-07T23:37:01.532664Z","title":"Gradient-based Explanations for Deep Learning Survival Models","venue":"stat.ML","work_id":"4148d82e-31af-49ce-b56c-c83a3cf791ad","year":2025},"citing_paper":{"arxiv_id":"2502.08821","last_updated":"2025-05-08T04:42:55Z","snapshot_observed_at":"2026-08-07T23:31:49.273273Z","submitted_at":"2025-02-12T22:24:49Z","title":"DejAIvu: Identifying and Explaining AI Art on the Web in Real-Time with Saliency Maps","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T23:37:01.343477Z"},"links":{"cited_paper":"/paper/2502.04970","citing_paper":"/paper/2502.08821"},"observation_digest":"sha256:90efb561ad1ec01d60e1365cc382086ee87ec5b7cdd2635650a02c86a8640b69","observation_id":"aba82160-9121-4974-a925-45a1ce2a5618","resolution":{"observed_at":"2026-08-07T23:37:01.536794Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2502.04970/citation-record","integrity":"/paper/2502.04970/integrity","json":"/paper/2502.04970/citation-record.json","paper":"/paper/2502.04970"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.442971Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.442971Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:596bf1c2669d6fb5faefa9279dff2d0d80767d61c436482fb6e9416a4cf36b74","observation_id":"ddf67e9d-24db-4d44-98b3-aa00eab28881","resolution":{"observed_at":"2026-08-08T20:51:47.442971Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.448891Z","title":"Gradient-based attribution methods","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.448891Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:928d660eb0a1c6112ff5def369611741788b40b377a83651fcabcabd98103d44","observation_id":"67d7fd89-6415-417e-a898-152416480dc2","resolution":{"observed_at":"2026-08-08T20:51:47.448891Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.453495Z","title":"M., Du, Y., Guendouz, Y., Wei, L., Mazo, C., Becker, B","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.453495Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:89e17678f9432a88b9754735008b815ac356080b8dc85198cd6c3a0ed84e4dfe","observation_id":"04ab6f2a-5e03-416d-a566-30b2d6e785ea","resolution":{"observed_at":"2026-08-08T20:51:47.453495Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.457868Z","title":"Generating survival times to simulate cox proportional hazards models","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.457868Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:313204b1148bb20055244041e6bac862f896446f47f3e890d1e739b3dfb5df8c","observation_id":"182bbe66-ef19-4b5f-bed4-7ed0ed0eb073","resolution":{"observed_at":"2026-08-08T20:51:47.457868Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.462650Z","title":"L., Wolfe, R., Moreno-Betancur, M., and Crowther, M","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.462650Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:37ccec6ca8f7629c68293bc47817fddd78298934e6b6fd4ce827f47421ef4aa7","observation_id":"8bf642ea-0052-41f0-94c6-17608aca0938","resolution":{"observed_at":"2026-08-08T20:51:47.462650Z","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":"2026-08-08T20:51:48.604444Z","title":"C., Lundberg, S","venue":null,"work_id":"0a04dbde-0791-4252-94b2-fbb44d6aeee0","year":2023},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.466987Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:cb0d1c32af05eb9e28d94ae9d01a34879bf37f67e1b8b24cd87960165221c5d8","observation_id":"9a021dfa-b143-419c-b7bf-d55658f1ae23","resolution":{"observed_at":"2026-08-08T20:51:48.608541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1371/journal.pcbi.1006076","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":null,"venue":"PLoS Computational Biology","work_id":"cc5c0b63-e60d-43df-aea6-a850a7b4ad65","year":2018},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.471028Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:13ad14bf7a6f7473a96c335f094efe6147f5432b21f42f949e98031b9db052a3","observation_id":"0700c0b4-d2e6-4bfa-ad25-19b1745ddff6","resolution":{"observed_at":"2026-08-08T20:51:47.820492Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1093/bioinformatics/btad113","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"J., Shu, M., Bekiranov, S., Zang, C., and Zhang, A","venue":"Bioinformatics","work_id":"1987382c-c785-4b97-887d-4b018a85eda1","year":2023},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.476000Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:77bfe19e21d7a24962af4057f8b19a8039584f73a7e6c6bd48e4d9aa3e05b38d","observation_id":"ab224b68-086b-40f1-85e7-324401561f4a","resolution":{"observed_at":"2026-08-08T20:51:47.807382Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.592011Z","title":null,"venue":null,"work_id":"71cd0f7a-1c62-4175-9d7b-6fd230f63525","year":2015},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.480305Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:2389f9156e4b1c36f8a5212fc371114e865fac1cfcc00e7786f00198419378b9","observation_id":"e15db3af-dabe-48fa-8f3e-d0aa09f48dee","resolution":{"observed_at":"2026-08-08T20:51:48.596107Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.578199Z","title":null,"venue":null,"work_id":"ad0928b8-8a1a-4fd9-b38c-d51989a896f3","year":1972},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.484269Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:df1aa0fc6272d43694380bcc3a0bf4813c34516b9f0c0eac29a6dd26a6274f5e","observation_id":"e342f932-d409-4f16-aadc-a610828cb55c","resolution":{"observed_at":"2026-08-08T20:51:48.582517Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.488197Z","title":"D., Sturmfels, P., Lundberg, S","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.488197Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:23aa87139adce9de39acbfcd634198e81b7c136c41422ec256a3a3003608fe24","observation_id":"eea0afca-d65d-4da3-b069-700a11ae2a0b","resolution":{"observed_at":"2026-08-08T20:51:47.488197Z","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":"10.1007/978-3-030-68763-2_14","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"C., Gromicho, M., de Carvalho, M., Vinga, S., and Carvalho, A","venue":"Lecture notes in computer science","work_id":"bf8eb1de-f866-437b-b24d-ed63702c821a","year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.492241Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:b1f27b55c8a584a013ddb6b11237573116680d53104de6543e8d279a4fc3c596","observation_id":"363b6804-e550-4aee-925d-c68a613a49e2","resolution":{"observed_at":"2026-08-08T20:51:47.786416Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.496322Z","title":"H., and Kang, M","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.496322Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:b3fa8297a26bfe37e48468fd7ffe32e54569fc4500258d1449a3824822056e55","observation_id":"0623967e-5e2a-4bfe-aac7-42bf1f0d9e0c","resolution":{"observed_at":"2026-08-08T20:51:47.496322Z","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":"10.1142/9789811215636_0032","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"C., Tsaku, N","venue":null,"work_id":"1ca2bfcf-3c0d-4e5a-93d8-e5ef8fa8c16b","year":2020},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.500912Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:f30928b1eadf5a2230dbfe920c7afc350963c6ce03684a3ecfb1d14482cbc4c7","observation_id":"565cbac1-3c7f-4d00-8cf0-9e3d7200129c","resolution":{"observed_at":"2026-08-08T20:51:47.773678Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.504895Z","title":"Deep residual learning for image recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.504895Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:b5ffc30cc2fff1a6a8c4ec8dbb5e7683a3966b14116bf230738e28f1a68628cb","observation_id":"ac5a50fa-2f03-4246-b6b7-c3d7193f1d96","resolution":{"observed_at":"2026-08-08T20:51:47.504895Z","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":"2026-08-08T20:51:48.564925Z","title":"Fast axiomatic attribution for neural networks","venue":null,"work_id":"b75f929c-ca19-4371-b3a0-25dd41eed385","year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.508872Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:9cc7401f96b4930920b2e3abfea9a3022dc4eb4050e4839842fe62a1bf783477","observation_id":"77a72ceb-313f-4b9a-ba56-982b8904f509","resolution":{"observed_at":"2026-08-08T20:51:48.568940Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.512954Z","title":"L., Shaham, U., Cloninger, A., Bates, J., Jiang, T., and Kluger, Y","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.512954Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:61caa0751f9b0ca6000bc6fa64d66cde32d7f9f9eec4a6b5545f15915dedf53e","observation_id":"7d06c4de-82b1-45a0-b41b-02571a6386b7","resolution":{"observed_at":"2026-08-08T20:51:47.512954Z","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":"10.18637/jss.v111.i08","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"and Wright, M","venue":"Journal of Statistical Software","work_id":"160624d8-bbcf-435c-9b43-d58f46ab8ca8","year":2024},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.516969Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:a8d330ec91810030c35c6daef99fa9600b9486606cb2a054a3adb7de8b7b3feb","observation_id":"66d39622-d038-4eef-aa03-badab75b38f4","resolution":{"observed_at":"2026-08-08T20:51:47.744829Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.552351Z","title":"and Wright, M","venue":null,"work_id":"d52d60f4-84f1-4939-bd08-498c0cefeb04","year":2024},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.520918Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:a699a9e4e3f170c84e88cc589d40f00b571a8ed1b19648926d7c22a4151f597a","observation_id":"8c221599-6cd7-4c08-84e1-5e2ebcf1f536","resolution":{"observed_at":"2026-08-08T20:51:48.556354Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2020.10616","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.347993Z","title":"S., Utkin, L","venue":null,"work_id":"ac625caf-e3d7-4b2f-93b8-a85ec1f511b8","year":2020},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.524811Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:4df8edb95fa48ff8996c6afe189d7eed689b623b02e5ab5c730884c4e251e0fb","observation_id":"47891c0b-8603-4839-8933-11eb99603efd","resolution":{"observed_at":"2026-08-08T20:51:48.354498Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2022.11023","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.263977Z","title":"SurvSHAP (t) : Time-dependent explanations of machine learning survival models","venue":null,"work_id":"1a147fdf-2544-4306-8189-b9556fea4068","year":2023},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.528681Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:5e5b059923da396dce044ce7863d01ad6b09f1a1b2d4907d8c41d87ce8d9f50c","observation_id":"5381b706-76cd-4fe2-92a8-78b196a623f7","resolution":{"observed_at":"2026-08-08T20:51:48.270687Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.539784Z","title":"Time-to-event prediction with neural networks and Cox regression","venue":null,"work_id":"d2e394dc-c753-4f8a-a2ca-fe3c0d78ff6c","year":2019},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.532425Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:e89a290181c64a30bf2dc83560c7cd03517a25fa6a15990035ea99845cb660c0","observation_id":"96d19b10-3749-435d-b602-c7b6f2dc369f","resolution":{"observed_at":"2026-08-08T20:51:48.543894Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2403.10250","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.181285Z","title":"H., Krzyziński, M., Spytek, M., Baniecki, H., Biecek, P., and Wright, M","venue":null,"work_id":"e5053759-0795-4703-a560-dd680c34ddb2","year":2024},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.536247Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:29167124f54ad9e7f4a5787fed889370e59275b691bd454663c5ffbd39583fef","observation_id":"f7e61b09-cdea-4e42-b003-bfe52a4a9ad1","resolution":{"observed_at":"2026-08-08T20:51:48.187785Z","resolver_source":"raw_fallback","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.540168Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.540168Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:ec2cebeb894f7cf6cb47c080477bd8f6e7ffa08ee0b35e2f61116029a1eff791","observation_id":"7a8cd9d5-3192-418a-a86d-03891704be59","resolution":{"observed_at":"2026-08-08T20:51:47.540168Z","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":"2026-08-08T20:51:48.526991Z","title":"Synthetic benchmarks for scientific research in explainable machine learning","venue":null,"work_id":"512e3384-0bed-4c42-801d-a3e506fd5959","year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.544394Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:a7fe8fe6a084c65c50239ce11960e47a74323655a0e9b31c96278b73eacadef8","observation_id":"0c84f5e9-8b10-4969-8337-8c6d1c6a1d61","resolution":{"observed_at":"2026-08-08T20:51:48.531218Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.514055Z","title":null,"venue":null,"work_id":"5cafae7f-6ee8-45ff-b37d-0f2885b13f6b","year":2017},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.548291Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:1587e11c4dc06fc12da3ee0d38fb8c5ff442ec35fc657f8c6b2ac02cdd70d005","observation_id":"bc4e26bf-9ea6-4cf7-b974-365d1674bcbf","resolution":{"observed_at":"2026-08-08T20:51:48.518156Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.552262Z","title":"A., Barnholtz-Sloan, J","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.552262Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:af72de1106405cda5eabb5b2c44e4abe67535de1977eca8c69d3487388b70453","observation_id":"23bdfe6b-fee2-443b-9270-dce9fda6edcd","resolution":{"observed_at":"2026-08-08T20:51:47.552262Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.556420Z","title":"Explaining nonlinear classification decisions with deep taylor decomposition","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.556420Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:4d5356ca257f0e53eb4e107d358e30932cfddbb29a55cf69afff5a1f42b72886","observation_id":"401465a0-8a87-4dd8-bd53-17d5ca9a4c1d","resolution":{"observed_at":"2026-08-08T20:51:47.556420Z","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":"10.1002/jmri.28743","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T00:03:40.895421Z","title":"W., Vollmuth, P., Foltyn-Dumitru, M., Sahm, F., Ahn, S","venue":"Journal of Magnetic Resonance Imaging","work_id":"af2f44a5-b29f-4dfd-b861-c2f7051a57f8","year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.560449Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:437a23d134f7b5b1822846867d19f5271aea67f9b2ff3431fc34b3eba0179c72","observation_id":"e43635c9-60e6-49fb-94e5-df3ff47545f7","resolution":{"observed_at":"2026-08-08T20:51:47.707051Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.564369Z","title":"Pytorch: An imperative style, high-performance deep learning library","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.564369Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:c6cc41de10f13c4d08b9a52859d846f0666279a0b6ca66936b7d404976abf471","observation_id":"80912561-042c-4e09-bc64-21028e594e75","resolution":{"observed_at":"2026-08-08T20:51:47.564369Z","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":"2026-08-08T20:51:48.491544Z","title":null,"venue":null,"work_id":"edda01a0-36b3-4fe7-b04b-d34c61179208","year":2022},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.568281Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:56d213979df739fb64017e4411688d0fe0a0dc47f89c285d4f8136a3b7768180","observation_id":"5ace15e1-4d96-4d2a-adde-46f7787e0257","resolution":{"observed_at":"2026-08-08T20:51:48.495750Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.478880Z","title":"why should i trust you?","venue":null,"work_id":"66c8780c-8522-4a43-91e8-813e3550d06e","year":2016},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.572344Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:970f7dea349d019053b40e639386fd398e79265a5ab36456abcf1ff08d8e340a","observation_id":"3eebe453-786b-459c-ba51-ef20b05e1b19","resolution":{"observed_at":"2026-08-08T20:51:48.482841Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1605.01713","last_updated":"2017-04-11T15:58:48Z","snapshot_observed_at":"2026-08-09T11:23:47.064687Z","submitted_at":"2016-05-05T19:52:32Z","title":"Not Just a Black Box: Learning Important Features Through Propagating Activation Differences","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1605.01713","snapshot_observed_at":"2026-08-08T20:51:47.579217Z","title":"Not just a black box: Learning important features through propagating activation differences","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.579217Z"},"links":{"cited_paper":"/paper/1605.01713","citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:da94f6817b2df3a229af6b6f43e77d77515d3968e41aa0285298505c99de8ed6","observation_id":"2da007bb-b1b1-4fb6-898d-5bb62ce3a706","resolution":{"observed_at":"2026-08-08T20:51:47.579217Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1312.6034","last_updated":"2014-04-19T11:54:52Z","snapshot_observed_at":"2026-07-06T03:31:30.452356Z","submitted_at":"2013-12-20T16:45:54Z","title":"Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1312.6034","snapshot_observed_at":"2026-08-08T20:51:47.584096Z","title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.584096Z"},"links":{"cited_paper":"/paper/1312.6034","citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:f39f63e66d2cf409f1a4769f7b4058e1bb6a704c5ab05e56acbcf3e3778b7e27","observation_id":"b673086a-15bc-4079-9ba7-c22ff2b6b767","resolution":{"observed_at":"2026-08-08T20:51:47.584096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1706.03825","last_updated":"2017-06-12T19:53:30Z","snapshot_observed_at":"2026-07-06T05:46:32.599765Z","submitted_at":"2017-06-12T19:53:30Z","title":"SmoothGrad: removing noise by adding noise","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1706.03825","snapshot_observed_at":"2026-08-08T20:51:47.588679Z","title":"Smoothgrad: Removing noise by adding noise","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.588679Z"},"links":{"cited_paper":"/paper/1706.03825","citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:cbfcb605a4ab64c3f9d5ca3454d645bd4913147e2d9ecdb46ba0fccb2a0cdfc9","observation_id":"cab97dea-df6f-4db5-a2ee-7c4ea1958bb0","resolution":{"observed_at":"2026-08-08T20:51:47.588679Z","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":"2026-08-08T20:51:48.466061Z","title":"Axiomatic attribution for deep networks","venue":null,"work_id":"3aef4298-8a83-4d72-987d-06d95bce5f2e","year":2017},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.593077Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:a8dfe404624d5c5e1907513a837919f7e7d7905daee07db816e479a19e9b3d5c","observation_id":"f87e3e43-19db-4e24-86f2-1ec872b83df2","resolution":{"observed_at":"2026-08-08T20:51:48.470201Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.452507Z","title":"Capsurv: Capsule network for survival analysis with whole slide pathological images","venue":null,"work_id":"29022bee-4543-4d58-a9c5-5aab5621d2aa","year":2019},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.597018Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:33e08359c4998d39d8f340f74399503c7cfc17cfffcf4aca5a9044663552aeec","observation_id":"952e077f-5c00-401e-85b0-7997cc6c0eaa","resolution":{"observed_at":"2026-08-08T20:51:48.457280Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.437182Z","title":"The importance of interpretability and visualization in machine learning for applications in medicine and health care","venue":null,"work_id":"9a500c17-a683-4758-84d1-ad4140fce352","year":2020},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.601243Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:6e71795da1e11d05d9b0c548a0a9824088c0c65322aa36680d2bdb72021535ed","observation_id":"c4647ccc-ebeb-411d-8273-3945ff72a202","resolution":{"observed_at":"2026-08-08T20:51:48.442448Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.605641Z","title":"and Longo, L","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.605641Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:33e150a84754a026bfa65eab3f0c8d9ceaf2007d03b036af233ab4ac820f2871","observation_id":"b546d794-25c9-4b12-9937-65b1a0992bdb","resolution":{"observed_at":"2026-08-08T20:51:47.605641Z","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":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:47.610036Z","title":"Deep learning for survival analysis: A review","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.610036Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:5d2b42a980ec5b417d1e6577c9311682f478653ba9008ff5484b76be043609aa","observation_id":"07d81cee-f2a6-4953-a8e5-4480e82576b0","resolution":{"observed_at":"2026-08-08T20:51:47.610036Z","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":"2018.28642","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.112922Z","title":null,"venue":null,"work_id":"844f5c41-baf0-48eb-9546-760fdb3b3723","year":2019},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.614490Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:a02a1b29b523b220f2fa8ef7ed7189f61fe635857cfdb6f670547d377393a1c2","observation_id":"5a36ae1e-cbbb-458c-8c7b-1d6fa16f0eed","resolution":{"observed_at":"2026-08-08T20:51:48.119417Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2016.78225","doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-08T20:51:48.020546Z","title":"Deep convolutional neural network for survival analysis with pathological images","venue":null,"work_id":"d7142c9f-7521-459f-ad31-8e58f36e5ace","year":2016},"citing_paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-08T20:51:47.618470Z"},"links":{"citing_paper":"/paper/2502.04970"},"observation_digest":"sha256:354287cbf1e1bb07709eb88ebd25d3c609bc08861a960f01084e2b8e5c5dca50","observation_id":"5a8fda77-7e2d-45af-a7c3-1bba586bc5b1","resolution":{"observed_at":"2026-08-08T20:51:48.027614Z","resolver_source":"raw_fallback","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2502.04970","last_updated":"2025-02-07T14:36:55Z","latest_version":1,"primary_category":"stat.ML","snapshot_observed_at":"2026-08-08T20:44:43.877688Z","submitted_at":"2025-02-07T14:36:55Z","title":"Gradient-based Explanations for Deep Learning Survival Models"},"reference_resolution":{"displayed":42,"state_counts":{"malformed_identifier":0,"metadata_mismatch":4,"parse_uncertain":0,"unresolved":22,"verified_exact":7,"verified_fuzzy":9},"total_outbound_references":42},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2502.04970."}