{"as_of":"2026-08-08T18:18:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:27f6f5255db6da85585897632e4e75a3aa583df42efa999111deb01c343ee4e2","coverage":[{"denominator":59,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":59,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T04:10:33.754191Z","state":"measured"},{"denominator":59,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":59,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2506.11615/citation-record","integrity":"/paper/2506.11615/integrity","json":"/paper/2506.11615/citation-record.json","paper":"/paper/2506.11615"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.687304Z","title":null,"venue":null,"work_id":"8107b189-c93d-42c6-bf65-791400a2e2f9","year":2012},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.463568Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:ef2a988620df93f5d623890871f0ad63864791539f4030b27b8b7f3f7600159c","observation_id":"d471514a-b369-4ce4-b388-568ccab381f4","resolution":{"observed_at":"2026-08-07T04:10:34.692107Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.468708Z","title":"Deep residual learning for im- age recognition","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.468708Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:63ae8cad9c9f027cfb08e082ed5a68c49e2bada057686487ee6da523f617dffd","observation_id":"70e42dba-7844-4098-a25b-d81fcace9c07","resolution":{"observed_at":"2026-08-07T04:10:33.468708Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-07T04:10:33.473867Z","title":"An image is worth 16x16 words: Transformers for image recognition at scale","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.473867Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:4321b46bb7e3ca7dd624c3f8a46f5efc072e938e8330199217c57648bae7f740","observation_id":"f0805b44-196e-45ce-8dd7-4db83124da5d","resolution":{"observed_at":"2026-08-07T04:10:33.473867Z","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":"2026-08-07T04:10:34.659095Z","title":"Bert: Pre-training of deep bidirectional transformers for language understanding","venue":null,"work_id":"6926db99-cf4f-40ef-8f87-cde8a019f89b","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.479639Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:c0a87ef68b6fa68d2d0c885aa1d5f7cc22597e814e532a67236e4be2c60383b3","observation_id":"93e41a0b-d5be-4b7f-9b28-1783b5f6bd58","resolution":{"observed_at":"2026-08-07T04:10:34.663626Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.642716Z","title":"Gomez, Lukasz Kaiser, and Illia Polosukhin","venue":null,"work_id":"f5597771-6ffa-4b72-a02c-3f8b586b0216","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.485337Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:64501af906a813989317a331e7bcc7726af0795ebe83bb2cf966da1cef25cc93","observation_id":"8f78dffa-43a4-4b38-b1f4-903038108313","resolution":{"observed_at":"2026-08-07T04:10:34.647719Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.490331Z","title":"Language models are few-shot learners","venue":null,"work_id":null,"year":1901},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.490331Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:d0f4288ce8b14ec605671b242a19dfbbc0831ecf4344470c5ea360cbb352985c","observation_id":"5aa25ef5-d72c-478e-bff4-e623403b9ddc","resolution":{"observed_at":"2026-08-07T04:10:33.490331Z","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":"2026-08-07T04:10:34.615024Z","title":"Speech recognition with deep recurrent neural networks","venue":null,"work_id":"7638aed4-93d1-4dd3-8218-49e7731240b2","year":2013},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.495521Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:9a08e05263a773c75ac6e4dd4b2d3b204ac4bb128e93f876da5db25dc1cdc962","observation_id":"74bba2fb-61b1-41d2-809f-9eecf1e41449","resolution":{"observed_at":"2026-08-07T04:10:34.620438Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.597799Z","title":"Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups","venue":null,"work_id":"b6d34ff0-ed35-4758-8c19-bbdf6b24ff6f","year":2012},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.500664Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a9f0fb1549f9d3b7b5b2b8d8b277969f625c820e16e1ee1c50ea138b502d0e87","observation_id":"0a7c2fc7-9f2e-4f72-a5cc-9bcdbb2b6fd4","resolution":{"observed_at":"2026-08-07T04:10:34.603546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1412.5567","last_updated":"2014-12-19T21:36:13Z","snapshot_observed_at":"2026-07-06T04:03:56.251710Z","submitted_at":"2014-12-17T20:39:45Z","title":"Deep Speech: Scaling up end-to-end speech recognition","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1412.5567","snapshot_observed_at":"2026-08-07T04:10:33.505003Z","title":"Deep speech: Scaling up end-to-end speech recognition","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.505003Z"},"links":{"cited_paper":"/paper/1412.5567","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a66a66f444c7ee9fd416dcefd0c21660ae1731bc809cd8bd77be68a49658ebc3","observation_id":"5b315267-2a3a-4c5c-98b3-e7d679d4fefd","resolution":{"observed_at":"2026-08-07T04:10:33.505003Z","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":"2026-08-07T04:10:34.582248Z","title":"Dermatologist-level classification of skin cancer with deep neural net- works","venue":null,"work_id":"6c0e37eb-7253-40eb-b51b-7747238dfaaf","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.511584Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:ba82912a2bcf35b743bb7541195ed5810f043a40f6146c119d413a80e410ea6c","observation_id":"f434976b-244c-40e9-adb2-502ba4c793e8","resolution":{"observed_at":"2026-08-07T04:10:34.587078Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.566914Z","title":"A survey on deep learning in medical image analysis","venue":null,"work_id":"e8329740-5c83-4488-8398-7b749c21c996","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.516238Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:b5519e701787b358b7f414eecb47a3eedd69ead09c65e1f6646b2c72772c3e8e","observation_id":"1e0abef5-de34-478a-88f6-97b312655812","resolution":{"observed_at":"2026-08-07T04:10:34.571762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.522230Z","title":"Human-level control through deep reinforcement learning","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.522230Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:ef4ee313bf63806a49052089aa860355bba6b46fafba41d77ea6aa730dc218e8","observation_id":"b35a6c3c-9607-46c7-b87c-3f30cbea4004","resolution":{"observed_at":"2026-08-07T04:10:33.522230Z","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":"2026-08-07T04:10:34.540638Z","title":"Mastering the game of go with deep neural networks and tree search","venue":null,"work_id":"bbe44c7e-3ecb-4865-b22d-f8a357a4b4b4","year":2016},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.527352Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:aaed6c8078b351b7ea77f8a524a1550cca74f6c95053acb29e84f135256d6a3a","observation_id":"12c03af6-2905-410e-8e19-9f0c21b1b4e3","resolution":{"observed_at":"2026-08-07T04:10:34.545193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1707.06347","last_updated":"2017-08-28T09:20:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2017-07-20T02:32:33Z","title":"Proximal Policy Optimization Algorithms","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1707.06347","snapshot_observed_at":"2026-08-07T04:10:33.532608Z","title":"Proximal policy optimization algorithms","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.532608Z"},"links":{"cited_paper":"/paper/1707.06347","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:672793be3dc89badf76a7de05377a54380bb32608c602c4fc32cfa25b3bccffe","observation_id":"7db03c4f-f1db-428a-80ad-e55beb18acff","resolution":{"observed_at":"2026-08-07T04:10:33.532608Z","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":"2026-08-07T04:10:34.526227Z","title":"Generative adversarial nets","venue":null,"work_id":"ce45ddf3-7024-4cdb-8f29-c3ab2af9b55e","year":2014},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.537352Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:ac524df5865ead4fc55136c3e1c273918f58da89a221200cf62c62d9156214ff","observation_id":"1c0054c9-fc66-4d0d-b166-8544b3727393","resolution":{"observed_at":"2026-08-07T04:10:34.530450Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.510820Z","title":"Evasion attacks against machine learning at test time","venue":null,"work_id":"49d1ce17-c123-4f71-9367-8005b6fcc663","year":2013},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.541983Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:2e74e239a1005d20b0bbd1ef34dae9b6013ed636f35164782056c571dafc9b31","observation_id":"2d8c0639-f833-4286-8a29-af6e88f3f0d6","resolution":{"observed_at":"2026-08-07T04:10:34.515957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.495124Z","title":"Classification in the presence of label noise: a survey","venue":null,"work_id":"0d623309-b4c8-4d4f-b4b6-bb49efd31077","year":2013},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.547292Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:59b4d20274d998eb060f147d676220eacc1f161acfe7dbc550456cc20c712847","observation_id":"4ad0f41f-76a4-41aa-8155-3a98ffb9dfab","resolution":{"observed_at":"2026-08-07T04:10:34.499724Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.14749","last_updated":"2021-11-07T13:04:04Z","snapshot_observed_at":"2026-08-04T22:08:50.379039Z","submitted_at":"2021-03-26T21:54:36Z","title":"Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2103.14749","snapshot_observed_at":"2026-08-07T04:10:33.552063Z","title":"Pervasive label errors in test sets destabilize machine learning benchmarks","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.552063Z"},"links":{"cited_paper":"/paper/2103.14749","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:98c1981718e8a2d0bd1b9f6862835f21953ac216401cb61a4c1320086c33d053","observation_id":"c983470c-c349-46e1-9e9a-ff4b00faa454","resolution":{"observed_at":"2026-08-07T04:10:33.552063Z","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":"2026-08-07T04:10:34.480103Z","title":"Selfie: Refurbishing unclean samples for robust deep learning","venue":null,"work_id":"7f668553-0ea4-4ee4-9215-9ea6cc2f3fca","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.557094Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:accdf08ffc131d4ebc090ba40cf331f3ba10e99c7f76d4d6260b2b9abc890a83","observation_id":"dedac9fe-ec00-46fd-b906-6899037aee13","resolution":{"observed_at":"2026-08-07T04:10:34.484468Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1705.10694","last_updated":"2018-02-26T16:51:57Z","snapshot_observed_at":"2026-08-04T16:36:51.205771Z","submitted_at":"2017-05-30T15:10:51Z","title":"Deep Learning is Robust to Massive Label Noise","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1705.10694","snapshot_observed_at":"2026-08-07T04:10:33.562594Z","title":"Deep learning is robust to massive label noise","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.562594Z"},"links":{"cited_paper":"/paper/1705.10694","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a1aaee7a8dbf810ba0d635a9e33ae12b68b16077dfc5c11d63d8dcfd9994b73e","observation_id":"2c626b29-1cf6-4a59-b7d4-50adb7f365f2","resolution":{"observed_at":"2026-08-07T04:10:33.562594Z","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":"2026-08-07T04:10:34.465470Z","title":"Mimic-iii, a freely accessible critical care database","venue":null,"work_id":"6d70465b-a985-4c90-8849-b7d8bc2abef1","year":2016},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.567419Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:79978d2b98dfea73da532ef9e91d4b8831baf975cebc9b8d71a6917d4579e1f1","observation_id":"df7ca4cd-7ab2-413b-ba3e-9a234234c7d6","resolution":{"observed_at":"2026-08-07T04:10:34.470080Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.449676Z","title":"A closer look at memorization in deep networks","venue":null,"work_id":"67e1c880-4ecd-4ea9-a6d8-07069110d95e","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.572414Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:298a8408953eae195f90d65538a4bb7d92b419b1a9d3dd44af8099372e2d364c","observation_id":"2685a423-d3f1-414b-ab43-2abb6d4bbe01","resolution":{"observed_at":"2026-08-07T04:10:34.454763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1611.03530","last_updated":"2017-02-26T19:36:40Z","snapshot_observed_at":"2026-08-01T16:56:59.989486Z","submitted_at":"2016-11-10T22:02:36Z","title":"Understanding deep learning requires rethinking generalization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1611.03530","snapshot_observed_at":"2026-08-07T04:10:33.576993Z","title":"Under- standing deep learning requires rethinking generalization","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.576993Z"},"links":{"cited_paper":"/paper/1611.03530","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:7989326ff50e52120401580469502c42e9793f83ea20c844225ed9fe1918abbd","observation_id":"734253e6-17df-4872-80e4-6b2dd1ad73f3","resolution":{"observed_at":"2026-08-07T04:10:33.576993Z","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":"2026-08-07T04:10:34.432653Z","title":"Reconciling modern machine- learning practice and the classical bias–variance trade-o ff","venue":null,"work_id":"5fb5aa7e-cfb7-42ae-bd10-70ae19dacd50","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.582169Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:7aba131746a0f02ed5a37cb96833cb75f2592039f1da106006a2b22948933e79","observation_id":"1e04b028-10bb-414f-8491-31381030a48e","resolution":{"observed_at":"2026-08-07T04:10:34.438219Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1606.06565","last_updated":"2016-07-25T17:23:29Z","snapshot_observed_at":"2026-07-06T05:00:46.434335Z","submitted_at":"2016-06-21T13:37:05Z","title":"Concrete Problems in AI Safety","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1606.06565","snapshot_observed_at":"2026-08-07T04:10:33.586954Z","title":"Concrete problems in ai safety","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.586954Z"},"links":{"cited_paper":"/paper/1606.06565","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:56faf9e00d29556983217510b47e75ace6988dbf31e3a94fe6e81afa388e69ec","observation_id":"8e6af645-c722-4967-b1c7-1c2b3baa325e","resolution":{"observed_at":"2026-08-07T04:10:33.586954Z","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":"2026-08-07T04:10:34.415916Z","title":"Cleannet: Transfer learning for scalable image classifier training with label noise","venue":null,"work_id":"efd8188b-9175-4e80-843f-0e731a897d8b","year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.592269Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:61179d913bb4b5c852f46a7de57e68c2ae4c92e249e1c7a4685ff38cbf3b4f12","observation_id":"8dd00622-7103-457f-bbb9-a1680f990f3a","resolution":{"observed_at":"2026-08-07T04:10:34.421480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.400097Z","title":"Tods: An automated time series outlier detection system","venue":null,"work_id":"4a0e26da-d01f-4bf5-9ebe-04418fe746b4","year":2021},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.597594Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:fffdab30406f35a93a030d04cb53258d851fb22dca8ec746d5d16b1ee606cdc9","observation_id":"83145bbc-4d41-4bb4-91fd-e5a4e98fdbf8","resolution":{"observed_at":"2026-08-07T04:10:34.405043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.384058Z","title":"Identifying mislabeled training data","venue":null,"work_id":"e4e55767-02c7-4b6e-be7e-5fd67e6e9585","year":1999},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.603846Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:3283506b1f47440b7330af12a472c477fe6d646f29d161ccc871cae7f68a0c76","observation_id":"bb7bfc07-652a-45e7-9ee8-04011db6e5f9","resolution":{"observed_at":"2026-08-07T04:10:34.388948Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.368618Z","title":"Symmetric cross entropy for robust learning with noisy labels","venue":null,"work_id":"bca82b80-510a-4b47-805f-42a2d44aa8d4","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.608655Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:6295c19f0006d807b1006788509bdf23ca9c7863d4a08fcb5115ffe581cf131d","observation_id":"142d642a-8d15-4f6e-b93b-625721de6d23","resolution":{"observed_at":"2026-08-07T04:10:34.373460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.613171Z","title":"Generalized cross entropy loss for training deep neural networks with noisy labels","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.613171Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:e6402e06ade2ff17104ccd0bd2457480b7246564465d29d3921d82e01cd04039","observation_id":"ebe7b934-34f5-4891-8f0b-bdd9cf5b184c","resolution":{"observed_at":"2026-08-07T04:10:33.613171Z","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":"2026-08-07T04:10:34.342610Z","title":"Dimensionality-driven learning with noisy labels","venue":null,"work_id":"3d881a55-d187-45ce-bbb9-d4727cfb20a3","year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.617903Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:c13a34fc6227e09078b45c4024f2221094acb2a15e8496c44298cbcee478fe30","observation_id":"11788201-3c50-41ff-89de-9dce341bcd04","resolution":{"observed_at":"2026-08-07T04:10:34.347365Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.622628Z","title":"Co-teaching: Robust training of deep neural networks with extremely noisy labels","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.622628Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:1e6173bd24d74516921d015a2d928aaee2c002e96cfb57e5f9e9efbe2ca826b8","observation_id":"e1a6e30e-6463-44d2-a974-320983ef0129","resolution":{"observed_at":"2026-08-07T04:10:33.622628Z","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":"2026-08-07T04:10:34.316413Z","title":"Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels","venue":null,"work_id":"6d22ad40-a9f6-4e38-9869-6e882876a06f","year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.627435Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:e00bf9c35917e2fc8ed7485d2c7cc606831d1e442db028b0c70dc5eba282de8a","observation_id":"08e27b49-204a-4d64-ad47-ffc3c49a146a","resolution":{"observed_at":"2026-08-07T04:10:34.321542Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.295573Z","title":"Making deep neural networks robust to label noise: A loss correction approach","venue":null,"work_id":"6a480fc0-ce49-48fc-bb6f-b3ec965dec8c","year":1944},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.632324Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:29a18d3d18c70693ec98d20c098676f4498777fcb7de6bed445beb0b47431fc2","observation_id":"62c57850-fa5a-4334-acf9-ba873a332511","resolution":{"observed_at":"2026-08-07T04:10:34.300374Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.637127Z","title":"Learning to reweight examples for robust deep learning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.637127Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:2dffe47bcd0beaa08b4bbc8a1b9e371091696216a0b1139b76e8d7c1b8fef031","observation_id":"9639e3e1-a0a9-48e6-b50d-d088168c6e81","resolution":{"observed_at":"2026-08-07T04:10:33.637127Z","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":"2026-08-07T04:10:33.641944Z","title":"Classification with noisy labels by importance reweighting","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.641944Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:44046565061a34352864650f29ed1fc74a2d5031e3f3317e51b571a94feb9b46","observation_id":"f23eb266-e2d3-4e3e-bfb4-e6c30d907b0d","resolution":{"observed_at":"2026-08-07T04:10:33.641944Z","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":"2026-08-07T04:10:33.646895Z","title":"Are anchor points really indispensable in label-noise learning? Advances in neural information processing systems, 32, 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.646895Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:8c707b513835903ec5786946a3427c6340e755b0b6dda5e6150f89f221b9cd5d","observation_id":"230c716b-8a55-45a4-9691-349dec0bfa6e","resolution":{"observed_at":"2026-08-07T04:10:33.646895Z","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":"2026-08-07T04:10:34.249430Z","title":"Learning to learn from noisy labeled data","venue":null,"work_id":"ae4b74e1-9220-4e7b-a775-37219e2708df","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.652243Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:459f261e837fe5e3dbba7fa61cff7ef88c66d466fc7870b908fe8a71f0419cc3","observation_id":"5ad5c7ca-412f-45d0-bc5e-59596a580321","resolution":{"observed_at":"2026-08-07T04:10:34.254482Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.232613Z","title":"Meta- weight-net: Learning an explicit mapping for sample weighting","venue":null,"work_id":"89c92e50-44c8-4122-90bb-2b4d87282ef8","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.656694Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:3326d2c37147a9292932406be2c841aad496662514b580e4a84fa72214a0d288","observation_id":"acc958e5-c1a3-40f7-847b-b5acca8f3d04","resolution":{"observed_at":"2026-08-07T04:10:34.237523Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.661027Z","title":"Towards making systems forget with machine unlearning","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.661027Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:e0f4ac5761431536b51601921b8acf6562f58d242470f6007fb817989c9ddd95","observation_id":"28449fc3-4e61-489c-9463-9c3e2a94c59f","resolution":{"observed_at":"2026-08-07T04:10:33.661027Z","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":"2026-08-07T04:10:34.206633Z","title":"Machine unlearning","venue":null,"work_id":"669269b8-cb2e-4020-b62a-4bc5d85abb73","year":2021},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.665681Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:784b42dcff6e152fde7cc82ddc2e6600e075adec625a6a2b23979f0cba38d35b","observation_id":"34c31683-2887-4e55-9fc5-0d9eea1ec956","resolution":{"observed_at":"2026-08-07T04:10:34.211083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.191039Z","title":"Amnesiac machine learning","venue":null,"work_id":"0b9b7264-b1e1-4169-8b31-cd37e7eabaa3","year":2021},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.671073Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a86c047a237972aa44c5d06aa5dfb1bab4f4550fe5ad3e69cc563a43b52e0491","observation_id":"e681f041-2deb-41e0-81eb-9c18b7508df3","resolution":{"observed_at":"2026-08-07T04:10:34.195642Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.175638Z","title":"On the necessity of au- ditable algorithmic definitions for machine unlearning","venue":null,"work_id":"46356056-c163-4152-a4fb-ed4afeb5f7b5","year":2022},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.675771Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a6168e3626c43f019779b3153dab6f930a61d621bdc7d6ccfee68536a3c75113","observation_id":"ea788675-5b75-43c6-bf3d-7c852df4d272","resolution":{"observed_at":"2026-08-07T04:10:34.180182Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.159572Z","title":"Eternal sunshine of the spotless net: Selective forgetting in deep networks","venue":null,"work_id":"4c3ec91f-b6ee-4517-a7e2-178c639c615b","year":2020},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.680615Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:2cd75329eca3b5130462698653a00a9921a445bf848da74350f4f940f691814f","observation_id":"c5450715-5c25-48ca-8cef-96909a051d9d","resolution":{"observed_at":"2026-08-07T04:10:34.164735Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:33.685493Z","title":"Axiomatic attribution for deep networks","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.685493Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:d6d7a5153bef4bcca9d46de164f6d9d1f427fc53468dd706c98b11da9b52092a","observation_id":"ccca1a42-c755-450c-9f69-5a1db81ef19c","resolution":{"observed_at":"2026-08-07T04:10:33.685493Z","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":"2026-08-07T04:10:33.689865Z","title":"Deep inside convolutional networks: Visualising image classification models and saliency maps","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.689865Z"},"links":{"cited_paper":"/paper/1312.6034","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:7399dcfee4b1987db63c159cad6671be5d2b62e749128d94027533c76949ba48","observation_id":"cef2ebfc-f588-4f9b-aa64-4afee49cdd5e","resolution":{"observed_at":"2026-08-07T04:10:33.689865Z","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":"2026-08-07T04:10:34.132165Z","title":"Learning both weights and connections for efficient neural networks","venue":null,"work_id":"ba3e5997-9cd9-44e6-b347-0e8b98c25b6e","year":2015},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.694702Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:a4b840376cbcbd9a5910416240cdc6ef391f250c2d6e4cd498feef2b1cfd4dac","observation_id":"56b8b891-8464-4fb7-987c-4f3892af1e48","resolution":{"observed_at":"2026-08-07T04:10:34.137535Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1712.01312","last_updated":"2018-06-22T14:54:59Z","snapshot_observed_at":"2026-07-06T06:12:42.842258Z","submitted_at":"2017-12-04T19:20:27Z","title":"Learning Sparse Neural Networks through $L_0$ Regularization","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1712.01312","snapshot_observed_at":"2026-08-07T04:10:33.699166Z","title":"Learning sparse neural networks through l_0 regularization","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.699166Z"},"links":{"cited_paper":"/paper/1712.01312","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:23c9a32dbed9c2a8f62567a57ca8493ffe39d2743dd43b0056e022cf18056fa3","observation_id":"a7e188ce-ec25-4d50-8428-c3bbd88737c3","resolution":{"observed_at":"2026-08-07T04:10:33.699166Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1801.06146","last_updated":"2018-05-23T09:23:47Z","snapshot_observed_at":"2026-08-06T18:01:48.915710Z","submitted_at":"2018-01-18T17:54:52Z","title":"Universal Language Model Fine-tuning for Text Classification","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.06146","snapshot_observed_at":"2026-08-07T04:10:33.704274Z","title":"Universal language model fine-tuning for text classifi- cation","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.704274Z"},"links":{"cited_paper":"/paper/1801.06146","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:39425c2790d7031423cd9667e4a3e16548f6602f3fd5fe1ac58f149ec51d56b2","observation_id":"570a0be7-6836-405f-8514-a4eb1accc564","resolution":{"observed_at":"2026-08-07T04:10:33.704274Z","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":"2026-08-07T04:10:34.115660Z","title":"Neural transfer learning for natural language processing","venue":null,"work_id":"6891f1b1-6a8f-4623-9a78-59cc310b6e48","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.713859Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:fc6b5462bc6381de50886cc5c35bd179e54ebef5239fe09d86cf844b699dbe47","observation_id":"1b7adb29-f10b-4286-9098-e9990aa9f83d","resolution":{"observed_at":"2026-08-07T04:10:34.120855Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.100226Z","title":"Zeiler and Rob Fergus","venue":null,"work_id":"cf5be946-4227-4568-a335-d7eba79cb585","year":2014},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.718458Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:5ca43d1fc0aa8ea6fc5d257ec9b6306102b023b12667d5b1855a8b37dc88b060","observation_id":"87acf4ca-befa-4326-8b55-2a64f0a672a5","resolution":{"observed_at":"2026-08-07T04:10:34.105230Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.083433Z","title":"Lundberg and Su-In Lee","venue":null,"work_id":"a0be8060-4572-44b9-8789-6093e9eb29ed","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.723221Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:36836e80981c7c62b3c0b0dcecba9dc3fee0781a8b2fbd6f90a5bcc3f795826d","observation_id":"43ac1979-8d16-474d-97f8-879a601683a2","resolution":{"observed_at":"2026-08-07T04:10:34.089051Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.066952Z","title":"Axiomatic attribution for deep networks","venue":null,"work_id":"0cd0cc21-7515-4a7e-9ce7-3470d38ee86e","year":2017},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.727673Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:03df5bc0b33fdcb9620b8eec3d627109c6bc8349c07ec603f01188c729a09965","observation_id":"334097e8-b90b-4747-ba9f-12bfde1e1d66","resolution":{"observed_at":"2026-08-07T04:10:34.071740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.051297Z","title":"Importance estimation for neural network pruning","venue":null,"work_id":"4361426a-d38f-4d1f-8728-da0dc7875f68","year":2019},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.732313Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:6faf036725ab3d5637e78730fd1fc456648a4364ceaba2d9dde762c1c2bcfc3e","observation_id":"3c14b974-3de5-4c58-9f79-65b3ad14600b","resolution":{"observed_at":"2026-08-07T04:10:34.056301Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1801.05787","last_updated":"2018-07-09T10:38:35Z","snapshot_observed_at":"2026-08-07T19:42:19.497303Z","submitted_at":"2018-01-17T18:34:33Z","title":"Faster gaze prediction with dense networks and Fisher pruning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1801.05787","snapshot_observed_at":"2026-08-07T04:10:33.736944Z","title":"Faster gaze prediction with dense networks and fisher pruning","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.736944Z"},"links":{"cited_paper":"/paper/1801.05787","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:9b370ff60f1cc3584aca13943b29516d5124abd68408df6a533f6aa51bad41a0","observation_id":"b9a61dda-e1d8-4204-9fb1-60a1666d41b0","resolution":{"observed_at":"2026-08-07T04:10:33.736944Z","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":"2026-08-07T04:10:34.033536Z","title":"Contributions to the mathematical theory of evolution","venue":null,"work_id":"39748c89-ad51-4d9a-bae0-0b81cd818418","year":null},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.741152Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:9625a37b684f144d2ccb9fbbd248eebad43d470dcc3ccf4fa4b9d24effe01d86","observation_id":"aabc153a-2c38-4a01-a78a-41f3943dad02","resolution":{"observed_at":"2026-08-07T04:10:34.038381Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.018246Z","title":"k-means++: The advantages of careful seeding","venue":null,"work_id":"314b7fc0-20a0-4c04-b18c-1fe6c61d804a","year":2006},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.745534Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:ec9e021938e4611f99d249f1a2fcb8416ed2a8f5cab022cdce5357557976fd04","observation_id":"3cb43035-c6c2-4d1d-90dd-a6f1ba3296a2","resolution":{"observed_at":"2026-08-07T04:10:34.023066Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T04:10:34.000160Z","title":"Maximum likelihood from incom- plete data via the em algorithm","venue":null,"work_id":"f1c7a606-b5b9-4cb7-a8ed-ede440dcb536","year":1977},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.749661Z"},"links":{"citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:46aa472a0513c22ed1e86300dcb13aaf0414a327787dadc8e745d1446f134b65","observation_id":"04b07f8b-5667-4d20-9d3f-94dd1f4c94a9","resolution":{"observed_at":"2026-08-07T04:10:34.006960Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.01267","last_updated":"2024-07-24T17:13:55Z","snapshot_observed_at":"2026-08-08T00:49:26.550027Z","submitted_at":"2024-03-02T17:10:44Z","title":"Dissecting Language Models: Machine Unlearning via Selective Pruning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.01267","snapshot_observed_at":"2026-08-07T04:10:33.754191Z","title":"Dissecting language models: Machine unlearning via selective pruning","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T04:10:33.754191Z"},"links":{"cited_paper":"/paper/2403.01267","citing_paper":"/paper/2506.11615"},"observation_digest":"sha256:cb7c8f06a1fa8a62118ac71d059a31d3d5c95ffa55ea3b4cc0fe38b984ac2007","observation_id":"d35f65b2-1a1d-436e-b97a-d2628f1ea212","resolution":{"observed_at":"2026-08-07T04:10:33.754191Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.11615","last_updated":"2025-06-13T09:37:11Z","latest_version":1,"primary_category":"cs.LG","snapshot_observed_at":"2026-08-08T15:17:29.552584Z","submitted_at":"2025-06-13T09:37:11Z","title":"Machine Unlearning for Robust DNNs: Attribution-Guided Partitioning and Neuron Pruning in Noisy Environments"},"reference_resolution":{"displayed":59,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":23,"verified_exact":0,"verified_fuzzy":36},"total_outbound_references":59},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 59 of 59 outbound references and 0 inbound Pith citation observations for arXiv:2506.11615."}