{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:IRSQTMUOKZXIRZRMLMXTRMJRHY","short_pith_number":"pith:IRSQTMUO","canonical_record":{"source":{"id":"2309.15048","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-26T16:25:57Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ec1844e177c4a2daef8d0e86ff42f1477a8721f9b241a43e3d29509647ab75c3","abstract_canon_sha256":"aa5a3d57e3a68467435030fea6b2b70b8e0d0eadbf268e520922d869f9f2ede3"},"schema_version":"1.0"},"canonical_sha256":"446509b28e566e88e62c5b2f38b1313e3c5e67ebe47d16deb72eb67bb0bb4069","source":{"kind":"arxiv","id":"2309.15048","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.15048","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"arxiv_version","alias_value":"2309.15048v4","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.15048","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_12","alias_value":"IRSQTMUOKZXI","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_16","alias_value":"IRSQTMUOKZXIRZRM","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_8","alias_value":"IRSQTMUO","created_at":"2026-07-05T07:55:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:IRSQTMUOKZXIRZRMLMXTRMJRHY","target":"record","payload":{"canonical_record":{"source":{"id":"2309.15048","kind":"arxiv","version":4},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-26T16:25:57Z","cross_cats_sorted":["cs.AI","cs.CV"],"title_canon_sha256":"ec1844e177c4a2daef8d0e86ff42f1477a8721f9b241a43e3d29509647ab75c3","abstract_canon_sha256":"aa5a3d57e3a68467435030fea6b2b70b8e0d0eadbf268e520922d869f9f2ede3"},"schema_version":"1.0"},"canonical_sha256":"446509b28e566e88e62c5b2f38b1313e3c5e67ebe47d16deb72eb67bb0bb4069","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:55:24.665768Z","signature_b64":"RNF7s/Zz/RjTWCZs91Y6M9Hd4UZTwJU7PFYeVbO0cQL0Ma/iA+0qSfyBdAafksg1hBk2MSVsh4L4+cwb8j4TDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"446509b28e566e88e62c5b2f38b1313e3c5e67ebe47d16deb72eb67bb0bb4069","last_reissued_at":"2026-07-05T07:55:24.665398Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:55:24.665398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.15048","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:55:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OSH6fOVZUyhHrFXXcpxs0SMU0x3bxY5SN9+FPA0KtedT8qzkbAD6PqlIJS4GoBAOGic6KjV53BkiXYF0HH2HCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:24:30.820298Z"},"content_sha256":"b58bdb07e88c477e66c9b41f095f0e855e9aa79e84b903a8c7153677259f0162","schema_version":"1.0","event_id":"sha256:b58bdb07e88c477e66c9b41f095f0e855e9aa79e84b903a8c7153677259f0162"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:IRSQTMUOKZXIRZRMLMXTRMJRHY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Class Incremental Learning via Likelihood Ratio Based Task Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CV"],"primary_cat":"cs.LG","authors_text":"Bing Liu, Haowei Lin, Ningxin Pan, Weinan Qian, Yiduo Guo, Yijia Shao","submitted_at":"2023-09-26T16:25:57Z","abstract_excerpt":"Class incremental learning (CIL) is a challenging setting of continual learning, which learns a series of tasks sequentially. Each task consists of a set of unique classes. The key feature of CIL is that no task identifier (or task-id) is provided at test time. Predicting the task-id for each test sample is a challenging problem. An emerging theory-guided approach (called TIL+OOD) is to train a task-specific model for each task in a shared network for all tasks based on a task-incremental learning (TIL) method to deal with catastrophic forgetting. The model for each task is an out-of-distribut"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.15048","kind":"arxiv","version":4},"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/2309.15048/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":"2026-07-05T07:55:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gXJth1oI6ciQmhRC/gI7EDx5HZ5Caniz/FxVmcgoyf6F3g2M4gxPLj8O/d6DWuMb+Ol2UlQqX8g5ARZIiIInCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T12:24:30.820692Z"},"content_sha256":"256bd5d47a2bd0ef519e5cf66e21280ad03931f99dda071019f11870da3f4e0e","schema_version":"1.0","event_id":"sha256:256bd5d47a2bd0ef519e5cf66e21280ad03931f99dda071019f11870da3f4e0e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/bundle.json","state_url":"https://pith.science/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/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":"2026-08-04T12:24:30Z","links":{"resolver":"https://pith.science/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY","bundle":"https://pith.science/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/bundle.json","state":"https://pith.science/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/IRSQTMUOKZXIRZRMLMXTRMJRHY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:IRSQTMUOKZXIRZRMLMXTRMJRHY","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":"aa5a3d57e3a68467435030fea6b2b70b8e0d0eadbf268e520922d869f9f2ede3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-26T16:25:57Z","title_canon_sha256":"ec1844e177c4a2daef8d0e86ff42f1477a8721f9b241a43e3d29509647ab75c3"},"schema_version":"1.0","source":{"id":"2309.15048","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.15048","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"arxiv_version","alias_value":"2309.15048v4","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.15048","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_12","alias_value":"IRSQTMUOKZXI","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_16","alias_value":"IRSQTMUOKZXIRZRM","created_at":"2026-07-05T07:55:24Z"},{"alias_kind":"pith_short_8","alias_value":"IRSQTMUO","created_at":"2026-07-05T07:55:24Z"}],"graph_snapshots":[{"event_id":"sha256:256bd5d47a2bd0ef519e5cf66e21280ad03931f99dda071019f11870da3f4e0e","target":"graph","created_at":"2026-07-05T07:55:24Z","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/2309.15048/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Class incremental learning (CIL) is a challenging setting of continual learning, which learns a series of tasks sequentially. Each task consists of a set of unique classes. The key feature of CIL is that no task identifier (or task-id) is provided at test time. Predicting the task-id for each test sample is a challenging problem. An emerging theory-guided approach (called TIL+OOD) is to train a task-specific model for each task in a shared network for all tasks based on a task-incremental learning (TIL) method to deal with catastrophic forgetting. The model for each task is an out-of-distribut","authors_text":"Bing Liu, Haowei Lin, Ningxin Pan, Weinan Qian, Yiduo Guo, Yijia Shao","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-26T16:25:57Z","title":"Class Incremental Learning via Likelihood Ratio Based Task Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.15048","kind":"arxiv","version":4},"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:b58bdb07e88c477e66c9b41f095f0e855e9aa79e84b903a8c7153677259f0162","target":"record","created_at":"2026-07-05T07:55:24Z","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":"aa5a3d57e3a68467435030fea6b2b70b8e0d0eadbf268e520922d869f9f2ede3","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-09-26T16:25:57Z","title_canon_sha256":"ec1844e177c4a2daef8d0e86ff42f1477a8721f9b241a43e3d29509647ab75c3"},"schema_version":"1.0","source":{"id":"2309.15048","kind":"arxiv","version":4}},"canonical_sha256":"446509b28e566e88e62c5b2f38b1313e3c5e67ebe47d16deb72eb67bb0bb4069","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"446509b28e566e88e62c5b2f38b1313e3c5e67ebe47d16deb72eb67bb0bb4069","first_computed_at":"2026-07-05T07:55:24.665398Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:55:24.665398Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RNF7s/Zz/RjTWCZs91Y6M9Hd4UZTwJU7PFYeVbO0cQL0Ma/iA+0qSfyBdAafksg1hBk2MSVsh4L4+cwb8j4TDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:55:24.665768Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.15048","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b58bdb07e88c477e66c9b41f095f0e855e9aa79e84b903a8c7153677259f0162","sha256:256bd5d47a2bd0ef519e5cf66e21280ad03931f99dda071019f11870da3f4e0e"],"state_sha256":"9feba3a9ee697fa8e499303225eaba79ba9eceba4ccde6f4eb2372b1fde1339f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4+cCYT+o5zsot0a1KsQbWmscZhVsxSsFHMoHeQ9tGhIoARreD2xjugQjUlHYzJT7nl+rikSjFcNNWZ3+S73rAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T12:24:30.823467Z","bundle_sha256":"cf66750e80d1e8b8ebc069a4de305f2b336e2c6fefcb55e95dbe113e4349057d"}}