{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:JTYWXGATLJ3QUUKB7AB63BJ2W5","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":"9014d05d9938643b4c682e10ef34d8374a7459e898449cb55221b5216e3c5718","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-10T19:01:02Z","title_canon_sha256":"cc1daebfe33c0c76b52ba76895c594ad768c3ef704847571a2ecb375f31eb090"},"schema_version":"1.0","source":{"id":"1805.04136","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1805.04136","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"arxiv_version","alias_value":"1805.04136v1","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1805.04136","created_at":"2026-05-18T00:16:13Z"},{"alias_kind":"pith_short_12","alias_value":"JTYWXGATLJ3Q","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_16","alias_value":"JTYWXGATLJ3QUUKB","created_at":"2026-05-18T12:32:31Z"},{"alias_kind":"pith_short_8","alias_value":"JTYWXGAT","created_at":"2026-05-18T12:32:31Z"}],"graph_snapshots":[{"event_id":"sha256:c37bb905b29f8b322c4399c04d1c199d4b8c9813b627c657bd4d19bfc8caab86","target":"graph","created_at":"2026-05-18T00:16:13Z","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"},"paper":{"abstract_excerpt":"In this paper, we present an unsupervised learning approach for analyzing facial behavior based on a deep generative model combined with a convolutional neural network (CNN). We jointly train a variational auto-encoder (VAE) and a generative adversarial network (GAN) to learn a powerful latent representation from footage of audiences viewing feature-length movies. We show that the learned latent representation successfully encodes meaningful signatures of behaviors related to audience engagement (smiling & laughing) and disengagement (yawning). Our results provide a proof of concept for a more","authors_text":"Leonhard Helminger, Rajitha Navarathna, Romann Weber, Suman Saha","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-10T19:01:02Z","title":"Unsupervised Deep Representations for Learning Audience Facial Behaviors"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1805.04136","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":"sha256:064b430133fb951bbdf69e692773727eb4328daa1f1a389afbe25dd8e3f082f8","target":"record","created_at":"2026-05-18T00:16:13Z","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":"9014d05d9938643b4c682e10ef34d8374a7459e898449cb55221b5216e3c5718","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-05-10T19:01:02Z","title_canon_sha256":"cc1daebfe33c0c76b52ba76895c594ad768c3ef704847571a2ecb375f31eb090"},"schema_version":"1.0","source":{"id":"1805.04136","kind":"arxiv","version":1}},"canonical_sha256":"4cf16b98135a770a5141f803ed853ab76ec001d7a7f59592b704fc38b5287851","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4cf16b98135a770a5141f803ed853ab76ec001d7a7f59592b704fc38b5287851","first_computed_at":"2026-05-18T00:16:13.544338Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:16:13.544338Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"sFKu969kOkRtkOmkCFlqGaKN/xFo4RsjdJnZpG+ers/2zdZnX5QbjRJxSuLCaomLu9s5W/uGK7B3mK5Opo9KBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:16:13.545044Z","signed_message":"canonical_sha256_bytes"},"source_id":"1805.04136","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:064b430133fb951bbdf69e692773727eb4328daa1f1a389afbe25dd8e3f082f8","sha256:c37bb905b29f8b322c4399c04d1c199d4b8c9813b627c657bd4d19bfc8caab86"],"state_sha256":"90cb70e3ed8f1bb98094c16f2b8ed54eff5ab2b7cbdee1482088c77d282321db"}