{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:CRWEGZGHDBDDOELE2PFKLEJN56","short_pith_number":"pith:CRWEGZGH","canonical_record":{"source":{"id":"2410.00911","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T17:58:06Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"318d257e65d1226d489edb331375eeff9704b4c137dbe01398099dbe00e6e2fb","abstract_canon_sha256":"cbc35378ad99979916d5ee7b625f991bf85d165a832215db75eed2820538837a"},"schema_version":"1.0"},"canonical_sha256":"146c4364c71846371164d3caa5912defbcfe19bf2cdb2acdd8e44e0864139e08","source":{"kind":"arxiv","id":"2410.00911","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.00911","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"arxiv_version","alias_value":"2410.00911v2","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.00911","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_12","alias_value":"CRWEGZGHDBDD","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_16","alias_value":"CRWEGZGHDBDDOELE","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_8","alias_value":"CRWEGZGH","created_at":"2026-07-05T10:23:56Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:CRWEGZGHDBDDOELE2PFKLEJN56","target":"record","payload":{"canonical_record":{"source":{"id":"2410.00911","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T17:58:06Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"318d257e65d1226d489edb331375eeff9704b4c137dbe01398099dbe00e6e2fb","abstract_canon_sha256":"cbc35378ad99979916d5ee7b625f991bf85d165a832215db75eed2820538837a"},"schema_version":"1.0"},"canonical_sha256":"146c4364c71846371164d3caa5912defbcfe19bf2cdb2acdd8e44e0864139e08","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:23:56.673387Z","signature_b64":"A9i7ZRp7xccrFDuxlQimvme9tmUzeAbX6lObqKAJJSYtbUE1YE4iBUO7wnYhiAUjnjSUI/MZ7xhaOTP3/XBJDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"146c4364c71846371164d3caa5912defbcfe19bf2cdb2acdd8e44e0864139e08","last_reissued_at":"2026-07-05T10:23:56.672625Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:23:56.672625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.00911","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":"2026-07-05T10:23:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+lSuipxYpELzgC8b45t74PSj3wl84kzxB26ppJJyl78LqbjbzinmlBBXr22I/zge+BXLSj2gaOCpWi2lZ7d7Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:53:22.810770Z"},"content_sha256":"0fb0a26fb26d46f4054670c6a89f402b2aa0ba982c1bb2a520107f13f754f97d","schema_version":"1.0","event_id":"sha256:0fb0a26fb26d46f4054670c6a89f402b2aa0ba982c1bb2a520107f13f754f97d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:CRWEGZGHDBDDOELE2PFKLEJN56","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Da-Wei Zhou, De-Chuan Zhan, Han-Jia Ye, Lijun Zhang, Zi-Wen Cai","submitted_at":"2024-10-01T17:58:06Z","abstract_excerpt":"Domain-Incremental Learning (DIL) involves the progressive adaptation of a model to new concepts across different domains. While recent advances in pre-trained models provide a solid foundation for DIL, learning new concepts often results in the catastrophic forgetting of pre-trained knowledge. Specifically, sequential model updates can overwrite both the representation and the classifier with knowledge from the latest domain. Thus, it is crucial to develop a representation and corresponding classifier that accommodate all seen domains throughout the learning process. To this end, we propose D"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.00911","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/2410.00911/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":"2026-07-05T10:23:56Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qMnTHH+xUA1J5NskPATCAXiDSoxaP60OcQvzdKLp52cyQ2MbELDXmol2SQGnpVwNih6MHNtQRF6IQ1YSHYVXCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:53:22.811407Z"},"content_sha256":"2c795970ae543351c5994f2fc97c13fd75c21254b49f06e46be7951647fce545","schema_version":"1.0","event_id":"sha256:2c795970ae543351c5994f2fc97c13fd75c21254b49f06e46be7951647fce545"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/CRWEGZGHDBDDOELE2PFKLEJN56/bundle.json","state_url":"https://pith.science/pith/CRWEGZGHDBDDOELE2PFKLEJN56/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/CRWEGZGHDBDDOELE2PFKLEJN56/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":"2026-08-08T18:53:22Z","links":{"resolver":"https://pith.science/pith/CRWEGZGHDBDDOELE2PFKLEJN56","bundle":"https://pith.science/pith/CRWEGZGHDBDDOELE2PFKLEJN56/bundle.json","state":"https://pith.science/pith/CRWEGZGHDBDDOELE2PFKLEJN56/state.json","well_known_bundle":"https://pith.science/.well-known/pith/CRWEGZGHDBDDOELE2PFKLEJN56/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:CRWEGZGHDBDDOELE2PFKLEJN56","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":"cbc35378ad99979916d5ee7b625f991bf85d165a832215db75eed2820538837a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T17:58:06Z","title_canon_sha256":"318d257e65d1226d489edb331375eeff9704b4c137dbe01398099dbe00e6e2fb"},"schema_version":"1.0","source":{"id":"2410.00911","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.00911","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"arxiv_version","alias_value":"2410.00911v2","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.00911","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_12","alias_value":"CRWEGZGHDBDD","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_16","alias_value":"CRWEGZGHDBDDOELE","created_at":"2026-07-05T10:23:56Z"},{"alias_kind":"pith_short_8","alias_value":"CRWEGZGH","created_at":"2026-07-05T10:23:56Z"}],"graph_snapshots":[{"event_id":"sha256:2c795970ae543351c5994f2fc97c13fd75c21254b49f06e46be7951647fce545","target":"graph","created_at":"2026-07-05T10:23:56Z","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/2410.00911/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Domain-Incremental Learning (DIL) involves the progressive adaptation of a model to new concepts across different domains. While recent advances in pre-trained models provide a solid foundation for DIL, learning new concepts often results in the catastrophic forgetting of pre-trained knowledge. Specifically, sequential model updates can overwrite both the representation and the classifier with knowledge from the latest domain. Thus, it is crucial to develop a representation and corresponding classifier that accommodate all seen domains throughout the learning process. To this end, we propose D","authors_text":"Da-Wei Zhou, De-Chuan Zhan, Han-Jia Ye, Lijun Zhang, Zi-Wen Cai","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T17:58:06Z","title":"Dual Consolidation for Pre-Trained Model-Based Domain-Incremental Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.00911","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":"sha256:0fb0a26fb26d46f4054670c6a89f402b2aa0ba982c1bb2a520107f13f754f97d","target":"record","created_at":"2026-07-05T10:23:56Z","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":"cbc35378ad99979916d5ee7b625f991bf85d165a832215db75eed2820538837a","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-10-01T17:58:06Z","title_canon_sha256":"318d257e65d1226d489edb331375eeff9704b4c137dbe01398099dbe00e6e2fb"},"schema_version":"1.0","source":{"id":"2410.00911","kind":"arxiv","version":2}},"canonical_sha256":"146c4364c71846371164d3caa5912defbcfe19bf2cdb2acdd8e44e0864139e08","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"146c4364c71846371164d3caa5912defbcfe19bf2cdb2acdd8e44e0864139e08","first_computed_at":"2026-07-05T10:23:56.672625Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:23:56.672625Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A9i7ZRp7xccrFDuxlQimvme9tmUzeAbX6lObqKAJJSYtbUE1YE4iBUO7wnYhiAUjnjSUI/MZ7xhaOTP3/XBJDw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:23:56.673387Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.00911","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:0fb0a26fb26d46f4054670c6a89f402b2aa0ba982c1bb2a520107f13f754f97d","sha256:2c795970ae543351c5994f2fc97c13fd75c21254b49f06e46be7951647fce545"],"state_sha256":"d7b27abb53c58f2adc4d0a763a73ba1fa270500b543659a575374aa4be5fea4a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LNBkhYnod4wmFDFPmmUclckdCRNJBQEDURlcw3969fZ/QrCk75kSJlWrIMe5kvTdRlz9/thXv5tk8uJRMY+4Dw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T18:53:22.818545Z","bundle_sha256":"1d41d9ced9dbd36deaa0208e3ede213428f0f661591f4957f65908815dcd7535"}}