{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:VPAUJ4JOXHXA7N7XZM437O5VSK","short_pith_number":"pith:VPAUJ4JO","canonical_record":{"source":{"id":"2309.04038","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-07T22:36:22Z","cross_cats_sorted":[],"title_canon_sha256":"6ab3570dd3dd1d7460b5f44d8ba01c73cb829778e6f828d160f365b6dc15de87","abstract_canon_sha256":"cc42e4ffec71fb2bfc61a0b7e37bf46bdb56f8eea8f8702ce22cf614097a1662"},"schema_version":"1.0"},"canonical_sha256":"abc144f12eb9ee0fb7f7cb39bfbbb592b534946b18a41957fece65ea6f99c14e","source":{"kind":"arxiv","id":"2309.04038","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.04038","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"arxiv_version","alias_value":"2309.04038v2","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.04038","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_12","alias_value":"VPAUJ4JOXHXA","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_16","alias_value":"VPAUJ4JOXHXA7N7X","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_8","alias_value":"VPAUJ4JO","created_at":"2026-07-05T08:34:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:VPAUJ4JOXHXA7N7XZM437O5VSK","target":"record","payload":{"canonical_record":{"source":{"id":"2309.04038","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-07T22:36:22Z","cross_cats_sorted":[],"title_canon_sha256":"6ab3570dd3dd1d7460b5f44d8ba01c73cb829778e6f828d160f365b6dc15de87","abstract_canon_sha256":"cc42e4ffec71fb2bfc61a0b7e37bf46bdb56f8eea8f8702ce22cf614097a1662"},"schema_version":"1.0"},"canonical_sha256":"abc144f12eb9ee0fb7f7cb39bfbbb592b534946b18a41957fece65ea6f99c14e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:34:05.734890Z","signature_b64":"NJqHsSjSMLXp+u+0K4AXsk3DmkFmKVaLCqpAdgzLmXvQbQ1bZ7tLIP+d/2z83g5RPzwZYyJsi8Q3YGf27LZlBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"abc144f12eb9ee0fb7f7cb39bfbbb592b534946b18a41957fece65ea6f99c14e","last_reissued_at":"2026-07-05T08:34:05.734412Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:34:05.734412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2309.04038","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":"2026-07-05T08:34:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P9unRhQgA6dieRGtY2c8xn/ghxZ1MbDbfSe47ip0nZVzKnlitT9O2bKYZ4UF0QU2stI0C+M1RpQ453t8sx6sCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T05:35:51.741604Z"},"content_sha256":"ac33f266ffaa08fe96432fa497166dd361ecd91ad132aa3dfe4fa000bcf2b011","schema_version":"1.0","event_id":"sha256:ac33f266ffaa08fe96432fa497166dd361ecd91ad132aa3dfe4fa000bcf2b011"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:VPAUJ4JOXHXA7N7XZM437O5VSK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Alex Kot, Changsheng Chen, Chenqi Kong, Haoliang Li, Rizhao Cai, Yongjian Hu, Zitong Yu","submitted_at":"2023-09-07T22:36:22Z","abstract_excerpt":"Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on deep learning models but their cross-domain generalization capabilities are often hindered by the domain shift problem, which arises due to different distributions between training and testing data. In this study, we develop a generalized FAS method under the Efficient Parameter Transfer Learning (EPTL) paradigm, where we adapt the pre-trained Vision Transformer models for the FAS task. During training, the adapter mod"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.04038","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/2309.04038/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":"2026-07-05T08:34:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eu5PWImPobP6b+CqvE/OLbSi9zfUO2lMhfoqe99DbbbR+5gm/RmraaHTwAOXCPGavNKmHaNUETUbDcNM7WKRBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T05:35:51.742121Z"},"content_sha256":"127221ce3823a40c9c304e9ef8fb706c72a447d3dcaf1ad49e9cca0690fc375d","schema_version":"1.0","event_id":"sha256:127221ce3823a40c9c304e9ef8fb706c72a447d3dcaf1ad49e9cca0690fc375d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/bundle.json","state_url":"https://pith.science/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/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":"2026-08-22T05:35:51Z","links":{"resolver":"https://pith.science/pith/VPAUJ4JOXHXA7N7XZM437O5VSK","bundle":"https://pith.science/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/bundle.json","state":"https://pith.science/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VPAUJ4JOXHXA7N7XZM437O5VSK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:VPAUJ4JOXHXA7N7XZM437O5VSK","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":"cc42e4ffec71fb2bfc61a0b7e37bf46bdb56f8eea8f8702ce22cf614097a1662","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-07T22:36:22Z","title_canon_sha256":"6ab3570dd3dd1d7460b5f44d8ba01c73cb829778e6f828d160f365b6dc15de87"},"schema_version":"1.0","source":{"id":"2309.04038","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2309.04038","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"arxiv_version","alias_value":"2309.04038v2","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2309.04038","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_12","alias_value":"VPAUJ4JOXHXA","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_16","alias_value":"VPAUJ4JOXHXA7N7X","created_at":"2026-07-05T08:34:05Z"},{"alias_kind":"pith_short_8","alias_value":"VPAUJ4JO","created_at":"2026-07-05T08:34:05Z"}],"graph_snapshots":[{"event_id":"sha256:127221ce3823a40c9c304e9ef8fb706c72a447d3dcaf1ad49e9cca0690fc375d","target":"graph","created_at":"2026-07-05T08:34:05Z","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/2309.04038/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Face Anti-Spoofing (FAS) aims to detect malicious attempts to invade a face recognition system by presenting spoofed faces. State-of-the-art FAS techniques predominantly rely on deep learning models but their cross-domain generalization capabilities are often hindered by the domain shift problem, which arises due to different distributions between training and testing data. In this study, we develop a generalized FAS method under the Efficient Parameter Transfer Learning (EPTL) paradigm, where we adapt the pre-trained Vision Transformer models for the FAS task. During training, the adapter mod","authors_text":"Alex Kot, Changsheng Chen, Chenqi Kong, Haoliang Li, Rizhao Cai, Yongjian Hu, Zitong Yu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-07T22:36:22Z","title":"S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokens"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2309.04038","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:ac33f266ffaa08fe96432fa497166dd361ecd91ad132aa3dfe4fa000bcf2b011","target":"record","created_at":"2026-07-05T08:34:05Z","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":"cc42e4ffec71fb2bfc61a0b7e37bf46bdb56f8eea8f8702ce22cf614097a1662","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-09-07T22:36:22Z","title_canon_sha256":"6ab3570dd3dd1d7460b5f44d8ba01c73cb829778e6f828d160f365b6dc15de87"},"schema_version":"1.0","source":{"id":"2309.04038","kind":"arxiv","version":2}},"canonical_sha256":"abc144f12eb9ee0fb7f7cb39bfbbb592b534946b18a41957fece65ea6f99c14e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"abc144f12eb9ee0fb7f7cb39bfbbb592b534946b18a41957fece65ea6f99c14e","first_computed_at":"2026-07-05T08:34:05.734412Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:34:05.734412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NJqHsSjSMLXp+u+0K4AXsk3DmkFmKVaLCqpAdgzLmXvQbQ1bZ7tLIP+d/2z83g5RPzwZYyJsi8Q3YGf27LZlBg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:34:05.734890Z","signed_message":"canonical_sha256_bytes"},"source_id":"2309.04038","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac33f266ffaa08fe96432fa497166dd361ecd91ad132aa3dfe4fa000bcf2b011","sha256:127221ce3823a40c9c304e9ef8fb706c72a447d3dcaf1ad49e9cca0690fc375d"],"state_sha256":"1b6441bd240181ecbf434164a0671ade5b6e328b4650b059e2d345c46d38b81d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CMmbm0an1Jpu36oXXNTexcKAZun25+xkyetktbWsVvWh5YyBY5VWD74nL0K9gxpAr7MGMQ/STtAqATehl9CHDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T05:35:51.745833Z","bundle_sha256":"048b8129726b44f0db45347411c6defe19f68af40648f91b18671d88a4181467"}}