{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:KHDNSXL57BLDMU677R6XT3B6UM","short_pith_number":"pith:KHDNSXL5","canonical_record":{"source":{"id":"2306.00863","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T16:23:22Z","cross_cats_sorted":[],"title_canon_sha256":"aaa4ac45d461ab8aae7c94772a4540a1d822d6d6924d34acf85290682438f45a","abstract_canon_sha256":"b9eda1f220f94fa9cffb769bd7baf53873fea4cd898b0167d11a710574f6b30e"},"schema_version":"1.0"},"canonical_sha256":"51c6d95d7df8563653dffc7d79ec3ea31cf715b25fc7d62e98a6821b7f0c3ef0","source":{"kind":"arxiv","id":"2306.00863","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00863","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00863v2","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00863","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_12","alias_value":"KHDNSXL57BLD","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_16","alias_value":"KHDNSXL57BLDMU67","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_8","alias_value":"KHDNSXL5","created_at":"2026-07-05T09:45:40Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:KHDNSXL57BLDMU677R6XT3B6UM","target":"record","payload":{"canonical_record":{"source":{"id":"2306.00863","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T16:23:22Z","cross_cats_sorted":[],"title_canon_sha256":"aaa4ac45d461ab8aae7c94772a4540a1d822d6d6924d34acf85290682438f45a","abstract_canon_sha256":"b9eda1f220f94fa9cffb769bd7baf53873fea4cd898b0167d11a710574f6b30e"},"schema_version":"1.0"},"canonical_sha256":"51c6d95d7df8563653dffc7d79ec3ea31cf715b25fc7d62e98a6821b7f0c3ef0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:45:40.168970Z","signature_b64":"WtdCz3nkTcw59kGtkkzlA3dE1/W6RWLXut0HH9E+QbMdZ0058HeiXRHN0sv4UhwphMd7xzA2ctVf1OidgEGuCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"51c6d95d7df8563653dffc7d79ec3ea31cf715b25fc7d62e98a6821b7f0c3ef0","last_reissued_at":"2026-07-05T09:45:40.168536Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:45:40.168536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2306.00863","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":"2026-07-05T09:45:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wi+Wj0z0324xEd5yqO2BGoXt3AhNPTHL/jIk9oaeluLftEXvx4v2yeMXg/FwzQ1cgVN1qfUUhNFeQfxChG+tCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T10:39:33.789073Z"},"content_sha256":"6852b80a5dac3fb13aca724e0c37431f9faffc9d32e3c34b182ac9f777f4d9ca","schema_version":"1.0","event_id":"sha256:6852b80a5dac3fb13aca724e0c37431f9faffc9d32e3c34b182ac9f777f4d9ca"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:KHDNSXL57BLDMU677R6XT3B6UM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Liqiang Nie, Rui Shao, Tianxing Wu, Ziwei Liu","submitted_at":"2023-06-01T16:23:22Z","abstract_excerpt":"Existing deepfake detection methods fail to generalize well to unseen or degraded samples, which can be attributed to the over-fitting of low-level forgery patterns. Here we argue that high-level semantics are also indispensable recipes for generalizable forgery detection. Recently, large pre-trained Vision Transformers (ViTs) have shown promising generalization capability. In this paper, we propose the first parameter-efficient tuning approach for deepfake detection, namely DeepFake-Adapter, to effectively and efficiently adapt the generalizable high-level semantics from large pre-trained ViT"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00863","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/2306.00863/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":"2026-07-05T09:45:40Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LrTTBx0U2oL9E1gzV426GmzXVIThhbBtQlanj3h8Km0C+IhryrX3EEy3YCxcQRd/3OpDcaS5WjMisNEmgSU9AQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T10:39:33.789566Z"},"content_sha256":"caef0ca4d269eda025deaf9e5c8e19acb84dcb66c5ef6a11a41df33d8e3cdd6f","schema_version":"1.0","event_id":"sha256:caef0ca4d269eda025deaf9e5c8e19acb84dcb66c5ef6a11a41df33d8e3cdd6f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KHDNSXL57BLDMU677R6XT3B6UM/bundle.json","state_url":"https://pith.science/pith/KHDNSXL57BLDMU677R6XT3B6UM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KHDNSXL57BLDMU677R6XT3B6UM/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":"2026-08-12T10:39:33Z","links":{"resolver":"https://pith.science/pith/KHDNSXL57BLDMU677R6XT3B6UM","bundle":"https://pith.science/pith/KHDNSXL57BLDMU677R6XT3B6UM/bundle.json","state":"https://pith.science/pith/KHDNSXL57BLDMU677R6XT3B6UM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KHDNSXL57BLDMU677R6XT3B6UM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:KHDNSXL57BLDMU677R6XT3B6UM","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":"b9eda1f220f94fa9cffb769bd7baf53873fea4cd898b0167d11a710574f6b30e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T16:23:22Z","title_canon_sha256":"aaa4ac45d461ab8aae7c94772a4540a1d822d6d6924d34acf85290682438f45a"},"schema_version":"1.0","source":{"id":"2306.00863","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2306.00863","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"arxiv_version","alias_value":"2306.00863v2","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.00863","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_12","alias_value":"KHDNSXL57BLD","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_16","alias_value":"KHDNSXL57BLDMU67","created_at":"2026-07-05T09:45:40Z"},{"alias_kind":"pith_short_8","alias_value":"KHDNSXL5","created_at":"2026-07-05T09:45:40Z"}],"graph_snapshots":[{"event_id":"sha256:caef0ca4d269eda025deaf9e5c8e19acb84dcb66c5ef6a11a41df33d8e3cdd6f","target":"graph","created_at":"2026-07-05T09:45:40Z","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/2306.00863/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Existing deepfake detection methods fail to generalize well to unseen or degraded samples, which can be attributed to the over-fitting of low-level forgery patterns. Here we argue that high-level semantics are also indispensable recipes for generalizable forgery detection. Recently, large pre-trained Vision Transformers (ViTs) have shown promising generalization capability. In this paper, we propose the first parameter-efficient tuning approach for deepfake detection, namely DeepFake-Adapter, to effectively and efficiently adapt the generalizable high-level semantics from large pre-trained ViT","authors_text":"Liqiang Nie, Rui Shao, Tianxing Wu, Ziwei Liu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T16:23:22Z","title":"DeepFake-Adapter: Dual-Level Adapter for DeepFake Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.00863","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":"sha256:6852b80a5dac3fb13aca724e0c37431f9faffc9d32e3c34b182ac9f777f4d9ca","target":"record","created_at":"2026-07-05T09:45:40Z","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":"b9eda1f220f94fa9cffb769bd7baf53873fea4cd898b0167d11a710574f6b30e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-06-01T16:23:22Z","title_canon_sha256":"aaa4ac45d461ab8aae7c94772a4540a1d822d6d6924d34acf85290682438f45a"},"schema_version":"1.0","source":{"id":"2306.00863","kind":"arxiv","version":2}},"canonical_sha256":"51c6d95d7df8563653dffc7d79ec3ea31cf715b25fc7d62e98a6821b7f0c3ef0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"51c6d95d7df8563653dffc7d79ec3ea31cf715b25fc7d62e98a6821b7f0c3ef0","first_computed_at":"2026-07-05T09:45:40.168536Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:45:40.168536Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"WtdCz3nkTcw59kGtkkzlA3dE1/W6RWLXut0HH9E+QbMdZ0058HeiXRHN0sv4UhwphMd7xzA2ctVf1OidgEGuCg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:45:40.168970Z","signed_message":"canonical_sha256_bytes"},"source_id":"2306.00863","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6852b80a5dac3fb13aca724e0c37431f9faffc9d32e3c34b182ac9f777f4d9ca","sha256:caef0ca4d269eda025deaf9e5c8e19acb84dcb66c5ef6a11a41df33d8e3cdd6f"],"state_sha256":"f72a0232e69572f616dc8e655602963df3b2ed1684a12ea8485cd155db7d0dcc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MH+LN2yG6Vu6sHBiVrAbrS309odj8V8qNeyd7nua3Hq0Es/hhrG9ywxARb0Wl9uF+TAgnvEnNVZ4ytRQ2vLPAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T10:39:33.793447Z","bundle_sha256":"1e40079f8cf57adbac7f0a89e4f2659baaff217bc373fc15ae1a9001f579e673"}}