{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:STN3VFCACEK5AN4ZSHGIJFLJVE","short_pith_number":"pith:STN3VFCA","canonical_record":{"source":{"id":"2207.00005","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-26T06:20:17Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"ee92a9b45545397545d8718aa3965fb292597bbc4c2c154ad3f9d444f4cb639d","abstract_canon_sha256":"575759dc8d11e1184b00f166b54e337a228a98800901f47708810a81db6466cc"},"schema_version":"1.0"},"canonical_sha256":"94dbba94401115d0379991cc849569a910611feef469fe433b8a22e15202d3a9","source":{"kind":"arxiv","id":"2207.00005","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.00005","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"arxiv_version","alias_value":"2207.00005v2","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.00005","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_12","alias_value":"STN3VFCACEK5","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_16","alias_value":"STN3VFCACEK5AN4Z","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_8","alias_value":"STN3VFCA","created_at":"2026-07-05T04:37:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:STN3VFCACEK5AN4ZSHGIJFLJVE","target":"record","payload":{"canonical_record":{"source":{"id":"2207.00005","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-26T06:20:17Z","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"title_canon_sha256":"ee92a9b45545397545d8718aa3965fb292597bbc4c2c154ad3f9d444f4cb639d","abstract_canon_sha256":"575759dc8d11e1184b00f166b54e337a228a98800901f47708810a81db6466cc"},"schema_version":"1.0"},"canonical_sha256":"94dbba94401115d0379991cc849569a910611feef469fe433b8a22e15202d3a9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:37:07.199755Z","signature_b64":"fn2ZontnPSDH/sKKmgok/SOrTrJxwa6tqpgkWdxQoD/7A3D/Vif5ji5tH0/Qy2I8SnFsP4uRMdrDLXEeAfAHAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"94dbba94401115d0379991cc849569a910611feef469fe433b8a22e15202d3a9","last_reissued_at":"2026-07-05T04:37:07.199285Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:37:07.199285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.00005","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":"2026-07-05T04:37:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"v4B+hzkBrxAOYDGbNcqJGRpJty1zmZyH9O+FiBrfcKTuVbtgb409dN9HdAs+cvnsK941QrO9DP+2TGWpIJaFAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T09:47:53.332123Z"},"content_sha256":"9ef05d00927cc81f2b7f7060e52a5cdfa463f9bf3b3d9ec22a55b4f54afeac84","schema_version":"1.0","event_id":"sha256:9ef05d00927cc81f2b7f7060e52a5cdfa463f9bf3b3d9ec22a55b4f54afeac84"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:STN3VFCACEK5AN4ZSHGIJFLJVE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Class Impression for Data-free Incremental Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG","eess.IV"],"primary_cat":"cs.CV","authors_text":"Purang Abolmaesumi, Sana Ayromlou, Teresa Tsang, Xiaoxiao Li","submitted_at":"2022-06-26T06:20:17Z","abstract_excerpt":"Standard deep learning-based classification approaches require collecting all samples from all classes in advance and are trained offline. This paradigm may not be practical in real-world clinical applications, where new classes are incrementally introduced through the addition of new data. Class incremental learning is a strategy allowing learning from such data. However, a major challenge is catastrophic forgetting, i.e., performance degradation on previous classes when adapting a trained model to new data. Prior methodologies to alleviate this challenge save a portion of training data requi"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.00005","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/2207.00005/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":"2026-07-05T04:37:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"INVM2TOtr9ew3YS2BM4CNOSNmX2NSDt6dIffi4APkl+k9N/ToJGqOu2AxUm/yF+SaMfghrQOj6WKd5UJ79rfDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-13T09:47:53.332521Z"},"content_sha256":"6d19e65cfb47f1f4d390d109cc0d36c69e9f52ce1c75867931e7ec1f3f2fa2d2","schema_version":"1.0","event_id":"sha256:6d19e65cfb47f1f4d390d109cc0d36c69e9f52ce1c75867931e7ec1f3f2fa2d2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/bundle.json","state_url":"https://pith.science/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/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":"2026-07-13T09:47:53Z","links":{"resolver":"https://pith.science/pith/STN3VFCACEK5AN4ZSHGIJFLJVE","bundle":"https://pith.science/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/bundle.json","state":"https://pith.science/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/STN3VFCACEK5AN4ZSHGIJFLJVE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:STN3VFCACEK5AN4ZSHGIJFLJVE","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":"575759dc8d11e1184b00f166b54e337a228a98800901f47708810a81db6466cc","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-26T06:20:17Z","title_canon_sha256":"ee92a9b45545397545d8718aa3965fb292597bbc4c2c154ad3f9d444f4cb639d"},"schema_version":"1.0","source":{"id":"2207.00005","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.00005","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"arxiv_version","alias_value":"2207.00005v2","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.00005","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_12","alias_value":"STN3VFCACEK5","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_16","alias_value":"STN3VFCACEK5AN4Z","created_at":"2026-07-05T04:37:07Z"},{"alias_kind":"pith_short_8","alias_value":"STN3VFCA","created_at":"2026-07-05T04:37:07Z"}],"graph_snapshots":[{"event_id":"sha256:6d19e65cfb47f1f4d390d109cc0d36c69e9f52ce1c75867931e7ec1f3f2fa2d2","target":"graph","created_at":"2026-07-05T04:37:07Z","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/2207.00005/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Standard deep learning-based classification approaches require collecting all samples from all classes in advance and are trained offline. This paradigm may not be practical in real-world clinical applications, where new classes are incrementally introduced through the addition of new data. Class incremental learning is a strategy allowing learning from such data. However, a major challenge is catastrophic forgetting, i.e., performance degradation on previous classes when adapting a trained model to new data. Prior methodologies to alleviate this challenge save a portion of training data requi","authors_text":"Purang Abolmaesumi, Sana Ayromlou, Teresa Tsang, Xiaoxiao Li","cross_cats":["cs.AI","cs.LG","eess.IV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-26T06:20:17Z","title":"Class Impression for Data-free Incremental Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.00005","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":"sha256:9ef05d00927cc81f2b7f7060e52a5cdfa463f9bf3b3d9ec22a55b4f54afeac84","target":"record","created_at":"2026-07-05T04:37:07Z","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":"575759dc8d11e1184b00f166b54e337a228a98800901f47708810a81db6466cc","cross_cats_sorted":["cs.AI","cs.LG","eess.IV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-06-26T06:20:17Z","title_canon_sha256":"ee92a9b45545397545d8718aa3965fb292597bbc4c2c154ad3f9d444f4cb639d"},"schema_version":"1.0","source":{"id":"2207.00005","kind":"arxiv","version":2}},"canonical_sha256":"94dbba94401115d0379991cc849569a910611feef469fe433b8a22e15202d3a9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"94dbba94401115d0379991cc849569a910611feef469fe433b8a22e15202d3a9","first_computed_at":"2026-07-05T04:37:07.199285Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:37:07.199285Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fn2ZontnPSDH/sKKmgok/SOrTrJxwa6tqpgkWdxQoD/7A3D/Vif5ji5tH0/Qy2I8SnFsP4uRMdrDLXEeAfAHAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T04:37:07.199755Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.00005","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9ef05d00927cc81f2b7f7060e52a5cdfa463f9bf3b3d9ec22a55b4f54afeac84","sha256:6d19e65cfb47f1f4d390d109cc0d36c69e9f52ce1c75867931e7ec1f3f2fa2d2"],"state_sha256":"afadbdc559f2b9f172dd25c5aea23f839abec1d8bb02112170a195edf7cd22bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xioDfa3OF2o9SpHG6yqZm43yoQDVkSb014OjDkN2HawQUmgj1xPYY07nioJj8g12IR1xsEUmQpEjWGb+dE1LBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-13T09:47:53.334630Z","bundle_sha256":"f44ef2973845992a91de3103dbc9c170bc7b624b412ed60bcb86db8c4f9fa772"}}