{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QOY6OJVC2BASI52ROZWYEZ5W5H","short_pith_number":"pith:QOY6OJVC","canonical_record":{"source":{"id":"2403.19137","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-28T04:15:58Z","cross_cats_sorted":[],"title_canon_sha256":"4b5ed7ba9bd554af9b8d956cdbedf9f21f69fe649fb452ce3a61db602a5b5347","abstract_canon_sha256":"de300c254bfb2647a221589cacae6ca6e97775d51cadc9261f67f8722f113bbc"},"schema_version":"1.0"},"canonical_sha256":"83b1e726a2d041247751766d8267b6e9db2f22109308bbf4bcb8cdaee5c17d87","source":{"kind":"arxiv","id":"2403.19137","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.19137","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"arxiv_version","alias_value":"2403.19137v3","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.19137","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_12","alias_value":"QOY6OJVC2BAS","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_16","alias_value":"QOY6OJVC2BASI52R","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_8","alias_value":"QOY6OJVC","created_at":"2026-07-05T09:28:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QOY6OJVC2BASI52ROZWYEZ5W5H","target":"record","payload":{"canonical_record":{"source":{"id":"2403.19137","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-28T04:15:58Z","cross_cats_sorted":[],"title_canon_sha256":"4b5ed7ba9bd554af9b8d956cdbedf9f21f69fe649fb452ce3a61db602a5b5347","abstract_canon_sha256":"de300c254bfb2647a221589cacae6ca6e97775d51cadc9261f67f8722f113bbc"},"schema_version":"1.0"},"canonical_sha256":"83b1e726a2d041247751766d8267b6e9db2f22109308bbf4bcb8cdaee5c17d87","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:28:48.702921Z","signature_b64":"e8zJcQgms0VLAUi7TAHttYdK0LqFhgfzYdPkYGi51nufW2z6Wm2u8C9/N8CiqmLi0xlYbpwc4tnnEHJ861j0Dw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83b1e726a2d041247751766d8267b6e9db2f22109308bbf4bcb8cdaee5c17d87","last_reissued_at":"2026-07-05T09:28:48.702429Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:28:48.702429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.19137","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:28:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V1zAsj/+KLZyGjO0Fw1SWEG614m4AFK1P6T8aRYjidlSnac5aF204jLjojrcDkHYCSiBan2ANjVh9RQkbrNFBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:23:38.772453Z"},"content_sha256":"8a1dc865f2665e56229f608ff1483034c3e3cc08f4e852dbe5f244b5d0a2a515","schema_version":"1.0","event_id":"sha256:8a1dc865f2665e56229f608ff1483034c3e3cc08f4e852dbe5f244b5d0a2a515"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QOY6OJVC2BASI52ROZWYEZ5W5H","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dong Gong, Lina Yao, Saurav Jha","submitted_at":"2024-03-28T04:15:58Z","abstract_excerpt":"Continual learning (CL) aims to help deep neural networks learn new knowledge while retaining what has been learned. Owing to their powerful generalizability, pre-trained vision-language models such as Contrastive Language-Image Pre-training (CLIP) have lately gained traction as practical CL candidates. However, the domain mismatch between the pre-training and the downstream CL tasks often calls for finetuning of the CLIP on the latter. Most existing finetuning methods exhibit deterministic nature. This makes them overlook the many possible interactions across the input modalities and deems th"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.19137","kind":"arxiv","version":3},"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/2403.19137/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":"2026-07-05T09:28:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y1PfZPovDZSMvVa/daU5klKc972UVVRM/YWijE03ARRyHZ7Ba+8GiOP9JSSIcrWYnQOXsZFfvcT3xDrAfdfLCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:23:38.772962Z"},"content_sha256":"0454eb692c1569c2b010b31b68b398524b36988eb9b9bf98c9380f5b8b5e9016","schema_version":"1.0","event_id":"sha256:0454eb692c1569c2b010b31b68b398524b36988eb9b9bf98c9380f5b8b5e9016"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/bundle.json","state_url":"https://pith.science/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/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":"2026-08-08T20:23:38Z","links":{"resolver":"https://pith.science/pith/QOY6OJVC2BASI52ROZWYEZ5W5H","bundle":"https://pith.science/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/bundle.json","state":"https://pith.science/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QOY6OJVC2BASI52ROZWYEZ5W5H/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QOY6OJVC2BASI52ROZWYEZ5W5H","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":"de300c254bfb2647a221589cacae6ca6e97775d51cadc9261f67f8722f113bbc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-28T04:15:58Z","title_canon_sha256":"4b5ed7ba9bd554af9b8d956cdbedf9f21f69fe649fb452ce3a61db602a5b5347"},"schema_version":"1.0","source":{"id":"2403.19137","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.19137","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"arxiv_version","alias_value":"2403.19137v3","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.19137","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_12","alias_value":"QOY6OJVC2BAS","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_16","alias_value":"QOY6OJVC2BASI52R","created_at":"2026-07-05T09:28:48Z"},{"alias_kind":"pith_short_8","alias_value":"QOY6OJVC","created_at":"2026-07-05T09:28:48Z"}],"graph_snapshots":[{"event_id":"sha256:0454eb692c1569c2b010b31b68b398524b36988eb9b9bf98c9380f5b8b5e9016","target":"graph","created_at":"2026-07-05T09:28:48Z","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/2403.19137/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continual learning (CL) aims to help deep neural networks learn new knowledge while retaining what has been learned. Owing to their powerful generalizability, pre-trained vision-language models such as Contrastive Language-Image Pre-training (CLIP) have lately gained traction as practical CL candidates. However, the domain mismatch between the pre-training and the downstream CL tasks often calls for finetuning of the CLIP on the latter. Most existing finetuning methods exhibit deterministic nature. This makes them overlook the many possible interactions across the input modalities and deems th","authors_text":"Dong Gong, Lina Yao, Saurav Jha","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-28T04:15:58Z","title":"CLAP4CLIP: Continual Learning with Probabilistic Finetuning for Vision-Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.19137","kind":"arxiv","version":3},"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":"sha256:8a1dc865f2665e56229f608ff1483034c3e3cc08f4e852dbe5f244b5d0a2a515","target":"record","created_at":"2026-07-05T09:28:48Z","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":"de300c254bfb2647a221589cacae6ca6e97775d51cadc9261f67f8722f113bbc","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-03-28T04:15:58Z","title_canon_sha256":"4b5ed7ba9bd554af9b8d956cdbedf9f21f69fe649fb452ce3a61db602a5b5347"},"schema_version":"1.0","source":{"id":"2403.19137","kind":"arxiv","version":3}},"canonical_sha256":"83b1e726a2d041247751766d8267b6e9db2f22109308bbf4bcb8cdaee5c17d87","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83b1e726a2d041247751766d8267b6e9db2f22109308bbf4bcb8cdaee5c17d87","first_computed_at":"2026-07-05T09:28:48.702429Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:28:48.702429Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"e8zJcQgms0VLAUi7TAHttYdK0LqFhgfzYdPkYGi51nufW2z6Wm2u8C9/N8CiqmLi0xlYbpwc4tnnEHJ861j0Dw==","signature_status":"signed_v1","signed_at":"2026-07-05T09:28:48.702921Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.19137","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8a1dc865f2665e56229f608ff1483034c3e3cc08f4e852dbe5f244b5d0a2a515","sha256:0454eb692c1569c2b010b31b68b398524b36988eb9b9bf98c9380f5b8b5e9016"],"state_sha256":"a15e40b014ce5a1a8afbd9c875ba2c3b2ec1bf40352edeb316acb06ff9e5169b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FGaSefawRUMKsM4ckRBXXfc/wSOuj/Sk7yd+Q4kng4Zc6eJzZAotvmFh9bkpQepXXamQVAchVTxdS9orGmWHCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:23:38.777071Z","bundle_sha256":"621daf89e710894a76f1bd43bb559a45cb36a053d41bc0a478dc481013971428"}}