{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VVVOQGKRN7XLEVMDMP44AQTVMW","short_pith_number":"pith:VVVOQGKR","canonical_record":{"source":{"id":"2509.09935","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-12T02:53:03Z","cross_cats_sorted":[],"title_canon_sha256":"58b840e5d756c94ebf73948d103fdd00b364023dc3fcdd10688908eb3257676e","abstract_canon_sha256":"5b3c2bc0c5f7ab15f0dd8766f82c4b2c3f06cc587060bee6c6924297d665783a"},"schema_version":"1.0"},"canonical_sha256":"ad6ae819516feeb2558363f9c04275658dc2910c1bb578455e386504a3bc2952","source":{"kind":"arxiv","id":"2509.09935","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09935","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09935v1","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09935","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"VVVOQGKRN7XL","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_16","alias_value":"VVVOQGKRN7XLEVMD","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_8","alias_value":"VVVOQGKR","created_at":"2026-07-05T12:09:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VVVOQGKRN7XLEVMDMP44AQTVMW","target":"record","payload":{"canonical_record":{"source":{"id":"2509.09935","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-12T02:53:03Z","cross_cats_sorted":[],"title_canon_sha256":"58b840e5d756c94ebf73948d103fdd00b364023dc3fcdd10688908eb3257676e","abstract_canon_sha256":"5b3c2bc0c5f7ab15f0dd8766f82c4b2c3f06cc587060bee6c6924297d665783a"},"schema_version":"1.0"},"canonical_sha256":"ad6ae819516feeb2558363f9c04275658dc2910c1bb578455e386504a3bc2952","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:09:52.403367Z","signature_b64":"0G2LxCBtrsr9KCOt/6JRypX8EBYdF6FBEjCy/SW0+/9IMA2DGOVw/PhQZjHGijLKzIgWhDFzz2ITG/6eu3IpBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad6ae819516feeb2558363f9c04275658dc2910c1bb578455e386504a3bc2952","last_reissued_at":"2026-07-05T12:09:52.402935Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:09:52.402935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2509.09935","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ryGIxE3av+/HDKwpvCfjSqGb8UjqCj2Q5yqq1EaoZ0S2+O9Yveyip3X7ciyLK58Vu3PbQ9CZKUOB5RLhb4GXAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T00:42:32.709218Z"},"content_sha256":"fec74ef79c1cf0543dd5343832d12910e7639e71394e3b8eb864d1837c6e2dd6","schema_version":"1.0","event_id":"sha256:fec74ef79c1cf0543dd5343832d12910e7639e71394e3b8eb864d1837c6e2dd6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VVVOQGKRN7XLEVMDMP44AQTVMW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SCoDA: Self-supervised Continual Domain Adaptation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chirayu Agrawal, Snehasis Mukherjee","submitted_at":"2025-09-12T02:53:03Z","abstract_excerpt":"Source-Free Domain Adaptation (SFDA) addresses the challenge of adapting a model to a target domain without access to the data of the source domain. Prevailing methods typically start with a source model pre-trained with full supervision and distill the knowledge by aligning instance-level features. However, these approaches, relying on cosine similarity over L2-normalized feature vectors, inadvertently discard crucial geometric information about the latent manifold of the source model. We introduce Self-supervised Continual Domain Adaptation (SCoDA) to address these limitations. We make two k"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09935","kind":"arxiv","version":1},"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/2509.09935/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":"2026-07-05T12:09:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cYKvBM+X7cGKGvCXbuzavihcgEGm3s+EKkLazZ2UmCaSpmWT8mYwMBCVGtMfF2iqC81MfSxCA6DjGvq6DNAOCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T00:42:32.709750Z"},"content_sha256":"24e163bc5aed470fef3a0509322a2a8f47859d786ebc2bc6b97a4ed23ba35cf0","schema_version":"1.0","event_id":"sha256:24e163bc5aed470fef3a0509322a2a8f47859d786ebc2bc6b97a4ed23ba35cf0"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/bundle.json","state_url":"https://pith.science/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/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":"2026-08-18T00:42:32Z","links":{"resolver":"https://pith.science/pith/VVVOQGKRN7XLEVMDMP44AQTVMW","bundle":"https://pith.science/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/bundle.json","state":"https://pith.science/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VVVOQGKRN7XLEVMDMP44AQTVMW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VVVOQGKRN7XLEVMDMP44AQTVMW","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":"5b3c2bc0c5f7ab15f0dd8766f82c4b2c3f06cc587060bee6c6924297d665783a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-12T02:53:03Z","title_canon_sha256":"58b840e5d756c94ebf73948d103fdd00b364023dc3fcdd10688908eb3257676e"},"schema_version":"1.0","source":{"id":"2509.09935","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2509.09935","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"arxiv_version","alias_value":"2509.09935v1","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.09935","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_12","alias_value":"VVVOQGKRN7XL","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_16","alias_value":"VVVOQGKRN7XLEVMD","created_at":"2026-07-05T12:09:52Z"},{"alias_kind":"pith_short_8","alias_value":"VVVOQGKR","created_at":"2026-07-05T12:09:52Z"}],"graph_snapshots":[{"event_id":"sha256:24e163bc5aed470fef3a0509322a2a8f47859d786ebc2bc6b97a4ed23ba35cf0","target":"graph","created_at":"2026-07-05T12:09:52Z","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/2509.09935/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Source-Free Domain Adaptation (SFDA) addresses the challenge of adapting a model to a target domain without access to the data of the source domain. Prevailing methods typically start with a source model pre-trained with full supervision and distill the knowledge by aligning instance-level features. However, these approaches, relying on cosine similarity over L2-normalized feature vectors, inadvertently discard crucial geometric information about the latent manifold of the source model. We introduce Self-supervised Continual Domain Adaptation (SCoDA) to address these limitations. We make two k","authors_text":"Chirayu Agrawal, Snehasis Mukherjee","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-12T02:53:03Z","title":"SCoDA: Self-supervised Continual Domain Adaptation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.09935","kind":"arxiv","version":1},"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:fec74ef79c1cf0543dd5343832d12910e7639e71394e3b8eb864d1837c6e2dd6","target":"record","created_at":"2026-07-05T12:09:52Z","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":"5b3c2bc0c5f7ab15f0dd8766f82c4b2c3f06cc587060bee6c6924297d665783a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-09-12T02:53:03Z","title_canon_sha256":"58b840e5d756c94ebf73948d103fdd00b364023dc3fcdd10688908eb3257676e"},"schema_version":"1.0","source":{"id":"2509.09935","kind":"arxiv","version":1}},"canonical_sha256":"ad6ae819516feeb2558363f9c04275658dc2910c1bb578455e386504a3bc2952","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ad6ae819516feeb2558363f9c04275658dc2910c1bb578455e386504a3bc2952","first_computed_at":"2026-07-05T12:09:52.402935Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:09:52.402935Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0G2LxCBtrsr9KCOt/6JRypX8EBYdF6FBEjCy/SW0+/9IMA2DGOVw/PhQZjHGijLKzIgWhDFzz2ITG/6eu3IpBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T12:09:52.403367Z","signed_message":"canonical_sha256_bytes"},"source_id":"2509.09935","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:fec74ef79c1cf0543dd5343832d12910e7639e71394e3b8eb864d1837c6e2dd6","sha256:24e163bc5aed470fef3a0509322a2a8f47859d786ebc2bc6b97a4ed23ba35cf0"],"state_sha256":"77244035d26c4ae96dc82e44ee9cac93f22dd05a245cdad0b40f29e279e9c809"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RflAH41x6g+/1kW9ea/8xF19m2Jo63i1dytC7mqH3bq8kIKr/8bVQoH2DR3MzuLPWrFi92aE6JvucQu7ybqPDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T00:42:32.715139Z","bundle_sha256":"0914209d943f7278ca211d36c8846c05018f6ac8fed6632912bd856dfadfc0ff"}}