{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:3GW3WMPQQGAEVWFNCCN4623XGQ","short_pith_number":"pith:3GW3WMPQ","canonical_record":{"source":{"id":"2303.09162","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T08:57:33Z","cross_cats_sorted":[],"title_canon_sha256":"112cbb09f0717a2023e90bda86f1201992599dc2d93a1b3cae12223d6c414580","abstract_canon_sha256":"97803fe5054553a839246f62aafe3483f78b5f92079fc71ba4da3b3395adee4e"},"schema_version":"1.0"},"canonical_sha256":"d9adbb31f081804ad8ad109bcf6b773427042abe66577a3c36c7d659c8ee6be0","source":{"kind":"arxiv","id":"2303.09162","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09162","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09162v1","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09162","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"3GW3WMPQQGAE","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"3GW3WMPQQGAEVWFN","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"3GW3WMPQ","created_at":"2026-07-05T05:51:49Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:3GW3WMPQQGAEVWFNCCN4623XGQ","target":"record","payload":{"canonical_record":{"source":{"id":"2303.09162","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T08:57:33Z","cross_cats_sorted":[],"title_canon_sha256":"112cbb09f0717a2023e90bda86f1201992599dc2d93a1b3cae12223d6c414580","abstract_canon_sha256":"97803fe5054553a839246f62aafe3483f78b5f92079fc71ba4da3b3395adee4e"},"schema_version":"1.0"},"canonical_sha256":"d9adbb31f081804ad8ad109bcf6b773427042abe66577a3c36c7d659c8ee6be0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:51:49.591582Z","signature_b64":"cHXSUM1lHxG9hH7lvKaa4p0q37WNafmfMVt6K5tkkgtSXSe5bLIg9/squv2MS7q1HER2k1dhFyGD7MA9sZtkAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d9adbb31f081804ad8ad109bcf6b773427042abe66577a3c36c7d659c8ee6be0","last_reissued_at":"2026-07-05T05:51:49.591023Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:51:49.591023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2303.09162","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":"2026-07-05T05:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CNB62zy3xfn5Sr1wBEV9oKxFnNsJuIlF3PKBgfJITR/JKDynLjSApysWnDbuwpqnDCrsTpjqQ+Zm84nD0/fOBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T06:13:22.659964Z"},"content_sha256":"a057e03b606d927c2dc593e6c7a36182314f858246b26a31d40381abe8d6bdc6","schema_version":"1.0","event_id":"sha256:a057e03b606d927c2dc593e6c7a36182314f858246b26a31d40381abe8d6bdc6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:3GW3WMPQQGAEVWFNCCN4623XGQ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EmotiEffNet Facial Features in Uni-task Emotion Recognition in Video at ABAW-5 competition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Andrey V. Savchenko","submitted_at":"2023-03-16T08:57:33Z","abstract_excerpt":"In this article, the results of our team for the fifth Affective Behavior Analysis in-the-wild (ABAW) competition are presented. The usage of the pre-trained convolutional networks from the EmotiEffNet family for frame-level feature extraction is studied. In particular, we propose an ensemble of a multi-layered perceptron and the LightAutoML-based classifier. The post-processing by smoothing the results for sequential frames is implemented. Experimental results for the large-scale Aff-Wild2 database demonstrate that our model achieves a much greater macro-averaged F1-score for facial expressio"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09162","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/2303.09162/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":"2026-07-05T05:51:49Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4XnRllWf9dj81wlw5S74LcWYLA/GYOQ9uuErZ0+RDZLgPlDwzYii9EiySQNH13v1OxqHcPUSr0RFKZOCAksjCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T06:13:22.660456Z"},"content_sha256":"86361ac4967f61ee1e8048db7c31f2ffac5f5b039ba1baf3b7369878ac1a2770","schema_version":"1.0","event_id":"sha256:86361ac4967f61ee1e8048db7c31f2ffac5f5b039ba1baf3b7369878ac1a2770"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/bundle.json","state_url":"https://pith.science/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/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":"2026-08-06T06:13:22Z","links":{"resolver":"https://pith.science/pith/3GW3WMPQQGAEVWFNCCN4623XGQ","bundle":"https://pith.science/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/bundle.json","state":"https://pith.science/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3GW3WMPQQGAEVWFNCCN4623XGQ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:3GW3WMPQQGAEVWFNCCN4623XGQ","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":"97803fe5054553a839246f62aafe3483f78b5f92079fc71ba4da3b3395adee4e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T08:57:33Z","title_canon_sha256":"112cbb09f0717a2023e90bda86f1201992599dc2d93a1b3cae12223d6c414580"},"schema_version":"1.0","source":{"id":"2303.09162","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2303.09162","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"arxiv_version","alias_value":"2303.09162v1","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.09162","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_12","alias_value":"3GW3WMPQQGAE","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_16","alias_value":"3GW3WMPQQGAEVWFN","created_at":"2026-07-05T05:51:49Z"},{"alias_kind":"pith_short_8","alias_value":"3GW3WMPQ","created_at":"2026-07-05T05:51:49Z"}],"graph_snapshots":[{"event_id":"sha256:86361ac4967f61ee1e8048db7c31f2ffac5f5b039ba1baf3b7369878ac1a2770","target":"graph","created_at":"2026-07-05T05:51:49Z","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/2303.09162/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In this article, the results of our team for the fifth Affective Behavior Analysis in-the-wild (ABAW) competition are presented. The usage of the pre-trained convolutional networks from the EmotiEffNet family for frame-level feature extraction is studied. In particular, we propose an ensemble of a multi-layered perceptron and the LightAutoML-based classifier. The post-processing by smoothing the results for sequential frames is implemented. Experimental results for the large-scale Aff-Wild2 database demonstrate that our model achieves a much greater macro-averaged F1-score for facial expressio","authors_text":"Andrey V. Savchenko","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T08:57:33Z","title":"EmotiEffNet Facial Features in Uni-task Emotion Recognition in Video at ABAW-5 competition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.09162","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:a057e03b606d927c2dc593e6c7a36182314f858246b26a31d40381abe8d6bdc6","target":"record","created_at":"2026-07-05T05:51:49Z","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":"97803fe5054553a839246f62aafe3483f78b5f92079fc71ba4da3b3395adee4e","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-03-16T08:57:33Z","title_canon_sha256":"112cbb09f0717a2023e90bda86f1201992599dc2d93a1b3cae12223d6c414580"},"schema_version":"1.0","source":{"id":"2303.09162","kind":"arxiv","version":1}},"canonical_sha256":"d9adbb31f081804ad8ad109bcf6b773427042abe66577a3c36c7d659c8ee6be0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d9adbb31f081804ad8ad109bcf6b773427042abe66577a3c36c7d659c8ee6be0","first_computed_at":"2026-07-05T05:51:49.591023Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:51:49.591023Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"cHXSUM1lHxG9hH7lvKaa4p0q37WNafmfMVt6K5tkkgtSXSe5bLIg9/squv2MS7q1HER2k1dhFyGD7MA9sZtkAw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:51:49.591582Z","signed_message":"canonical_sha256_bytes"},"source_id":"2303.09162","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a057e03b606d927c2dc593e6c7a36182314f858246b26a31d40381abe8d6bdc6","sha256:86361ac4967f61ee1e8048db7c31f2ffac5f5b039ba1baf3b7369878ac1a2770"],"state_sha256":"ea8ae09e090f5574383784884d9aaef65554f57bd5ea03f5060003de8729764f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"vjVLDkN9MZQvexmAMwdmxn2ug1gHwHUAZMLkeykvSm2DuTSHizHxAyWBYntoeXdpAGfDu0ruLvhAuKQ3OZDcAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T06:13:22.664187Z","bundle_sha256":"78cae14420b30c51e84cf97bbc09ed485374ddb93af7eb0e4ce8dd2bc878f9ca"}}