{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:BULI5CK34NUS56ZOFO7TRU7HNE","short_pith_number":"pith:BULI5CK3","canonical_record":{"source":{"id":"2405.15517","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-05-24T13:01:35Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"ff5f091fa7bf5b6d24905da93a64ec0988836d2bb0851ad4d8125250cd727c17","abstract_canon_sha256":"7018f4d84e42ef9f52d261a4ac57b3104b20dc206e9477aa5911cc31ae32e3b5"},"schema_version":"1.0"},"canonical_sha256":"0d168e895be3692efb2e2bbf38d3e7690591758e21c07d058afb5c5a0b14b108","source":{"kind":"arxiv","id":"2405.15517","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.15517","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"arxiv_version","alias_value":"2405.15517v2","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.15517","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_12","alias_value":"BULI5CK34NUS","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_16","alias_value":"BULI5CK34NUS56ZO","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_8","alias_value":"BULI5CK3","created_at":"2026-07-05T08:33:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:BULI5CK34NUS56ZOFO7TRU7HNE","target":"record","payload":{"canonical_record":{"source":{"id":"2405.15517","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-05-24T13:01:35Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"ff5f091fa7bf5b6d24905da93a64ec0988836d2bb0851ad4d8125250cd727c17","abstract_canon_sha256":"7018f4d84e42ef9f52d261a4ac57b3104b20dc206e9477aa5911cc31ae32e3b5"},"schema_version":"1.0"},"canonical_sha256":"0d168e895be3692efb2e2bbf38d3e7690591758e21c07d058afb5c5a0b14b108","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:33:40.146117Z","signature_b64":"2zhAK30XDVN6B+242ca0rE89AKEK360/ivZONbFpJTqu4yUJCCrZR+nWhZUv59FBs8bGPso/KzOdQaXJeCehDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0d168e895be3692efb2e2bbf38d3e7690591758e21c07d058afb5c5a0b14b108","last_reissued_at":"2026-07-05T08:33:40.145583Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:33:40.145583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.15517","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:33:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2WUjwx9Bw5jfJEosgnixsVUkYHfMqCnIRmhA03b1xd05Rj3DWV2mqcV62c3TU3gTWHDTiOWlL26mj1l0sg/wAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:51:26.222874Z"},"content_sha256":"fbd10261c5eec06dae436025ad20a2488073871dc01a82200057b17751641527","schema_version":"1.0","event_id":"sha256:fbd10261c5eec06dae436025ad20a2488073871dc01a82200057b17751641527"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:BULI5CK34NUS56ZOFO7TRU7HNE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"eess.IV","authors_text":"Jingshuai Liu, Sotirios A. Tsaftaris, Steven McDonagh, Yuyang Xue","submitted_at":"2024-05-24T13:01:35Z","abstract_excerpt":"Machine unlearning is a promising paradigm for removing unwanted data samples from a trained model, towards ensuring compliance with privacy regulations and limiting harmful biases. Although unlearning has been shown in, e.g., classification and recommendation systems, its potential in medical image-to-image translation, specifically in image recon-struction, has not been thoroughly investigated. This paper shows that machine unlearning is possible in MRI tasks and has the potential to benefit for bias removal. We set up a protocol to study how much shared knowledge exists between datasets of "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.15517","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2405.15517/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:33:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"46go84jJE4J4b5kLNHlMIjaq+0iqawuRi3labUC8dlAkPMCCscZS0uzyKgRMLbXnsakE8fT4mYu9CGSMvek/Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-17T18:51:26.228195Z"},"content_sha256":"faae88ec48a80bd8cb427b810d2d14a82a4bb3bf920934c2f319246531359b93","schema_version":"1.0","event_id":"sha256:faae88ec48a80bd8cb427b810d2d14a82a4bb3bf920934c2f319246531359b93"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/BULI5CK34NUS56ZOFO7TRU7HNE/bundle.json","state_url":"https://pith.science/pith/BULI5CK34NUS56ZOFO7TRU7HNE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/BULI5CK34NUS56ZOFO7TRU7HNE/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-17T18:51:26Z","links":{"resolver":"https://pith.science/pith/BULI5CK34NUS56ZOFO7TRU7HNE","bundle":"https://pith.science/pith/BULI5CK34NUS56ZOFO7TRU7HNE/bundle.json","state":"https://pith.science/pith/BULI5CK34NUS56ZOFO7TRU7HNE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/BULI5CK34NUS56ZOFO7TRU7HNE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BULI5CK34NUS56ZOFO7TRU7HNE","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"7018f4d84e42ef9f52d261a4ac57b3104b20dc206e9477aa5911cc31ae32e3b5","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-05-24T13:01:35Z","title_canon_sha256":"ff5f091fa7bf5b6d24905da93a64ec0988836d2bb0851ad4d8125250cd727c17"},"schema_version":"1.0","source":{"id":"2405.15517","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.15517","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"arxiv_version","alias_value":"2405.15517v2","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.15517","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_12","alias_value":"BULI5CK34NUS","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_16","alias_value":"BULI5CK34NUS56ZO","created_at":"2026-07-05T08:33:40Z"},{"alias_kind":"pith_short_8","alias_value":"BULI5CK3","created_at":"2026-07-05T08:33:40Z"}],"graph_snapshots":[{"event_id":"sha256:faae88ec48a80bd8cb427b810d2d14a82a4bb3bf920934c2f319246531359b93","target":"graph","created_at":"2026-07-05T08:33:40Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2405.15517/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine unlearning is a promising paradigm for removing unwanted data samples from a trained model, towards ensuring compliance with privacy regulations and limiting harmful biases. Although unlearning has been shown in, e.g., classification and recommendation systems, its potential in medical image-to-image translation, specifically in image recon-struction, has not been thoroughly investigated. This paper shows that machine unlearning is possible in MRI tasks and has the potential to benefit for bias removal. We set up a protocol to study how much shared knowledge exists between datasets of ","authors_text":"Jingshuai Liu, Sotirios A. Tsaftaris, Steven McDonagh, Yuyang Xue","cross_cats":["cs.CV","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-05-24T13:01:35Z","title":"Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.15517","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:fbd10261c5eec06dae436025ad20a2488073871dc01a82200057b17751641527","target":"record","created_at":"2026-07-05T08:33:40Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"7018f4d84e42ef9f52d261a4ac57b3104b20dc206e9477aa5911cc31ae32e3b5","cross_cats_sorted":["cs.CV","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.IV","submitted_at":"2024-05-24T13:01:35Z","title_canon_sha256":"ff5f091fa7bf5b6d24905da93a64ec0988836d2bb0851ad4d8125250cd727c17"},"schema_version":"1.0","source":{"id":"2405.15517","kind":"arxiv","version":2}},"canonical_sha256":"0d168e895be3692efb2e2bbf38d3e7690591758e21c07d058afb5c5a0b14b108","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0d168e895be3692efb2e2bbf38d3e7690591758e21c07d058afb5c5a0b14b108","first_computed_at":"2026-07-05T08:33:40.145583Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:33:40.145583Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"2zhAK30XDVN6B+242ca0rE89AKEK360/ivZONbFpJTqu4yUJCCrZR+nWhZUv59FBs8bGPso/KzOdQaXJeCehDg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:33:40.146117Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.15517","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fbd10261c5eec06dae436025ad20a2488073871dc01a82200057b17751641527","sha256:faae88ec48a80bd8cb427b810d2d14a82a4bb3bf920934c2f319246531359b93"],"state_sha256":"5d9d5e11a5559b9706aec75a588e9f41ec906ed21decb665b88468ca78ba02f8"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MvvfFUSbZAXaV6qTLgWYcZJRWJ/KoX3xVxheDxbWmyoQcWwnQHwvcEMKrTPAU3NXxb0HMw8kkjjg3HeTj3RKDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-17T18:51:26.256184Z","bundle_sha256":"cf258d3d65b381d53e190f6c0aaf214c7ef79df511ef253448ec420df8ebf5e4"}}