{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:XHLBJDBC4XEECO4T3H27IMVL5S","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":"b45a1660f5d2a5df403593ee099fdb36efde54c32737b7340bdf7a98ed3340f0","cross_cats_sorted":["cs.HC","cs.MM"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2026-06-09T12:03:42Z","title_canon_sha256":"7751fe3d63cb9b68f15c7a7e85ecae2a6b306364e08789b03245126455a76107"},"schema_version":"1.0","source":{"id":"2606.10753","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.10753","created_at":"2026-06-10T01:10:38Z"},{"alias_kind":"arxiv_version","alias_value":"2606.10753v1","created_at":"2026-06-10T01:10:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.10753","created_at":"2026-06-10T01:10:38Z"},{"alias_kind":"pith_short_12","alias_value":"XHLBJDBC4XEE","created_at":"2026-06-10T01:10:38Z"},{"alias_kind":"pith_short_16","alias_value":"XHLBJDBC4XEECO4T","created_at":"2026-06-10T01:10:38Z"},{"alias_kind":"pith_short_8","alias_value":"XHLBJDBC","created_at":"2026-06-10T01:10:38Z"}],"graph_snapshots":[{"event_id":"sha256:02575de55c36e6806463b08dd06ac46e9e552ad3250e9f3dc3ded7ebfd0fcaa7","target":"graph","created_at":"2026-06-10T01:10:38Z","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/2606.10753/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Speech-driven 3D facial animation research has shown promising results, but most methods rely on representations that are not compatible with production pipelines. In this work, we present a deployable system that bridges this gap by enabling speech-driven 3D facial animation directly in Unreal Engine (UE) using ARKit-compatible representations. We construct 3DMEAD-ARKit dataset by converting the MEAD corpus into blendshape sequences using MediaPipe, and retrain FaceDiffuser and ProbTalk3D-X to generate stochastic and emotion controllable animations. We further develop a modular UE plugin with","authors_text":"Alessandro Busacchi, Kazi Injamamul Haque, Zerrin Yumak","cross_cats":["cs.HC","cs.MM"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2026-06-09T12:03:42Z","title":"Deploying Speech-Driven 3D Facial Animation in Unreal Engine for Production-Ready Digital Humans"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.10753","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":"sha256:2cd7143fb174b21eb3c3c415d320d31196bfc0f1d639acd71b1686465ca9c4b7","target":"record","created_at":"2026-06-10T01:10:38Z","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":"b45a1660f5d2a5df403593ee099fdb36efde54c32737b7340bdf7a98ed3340f0","cross_cats_sorted":["cs.HC","cs.MM"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.GR","submitted_at":"2026-06-09T12:03:42Z","title_canon_sha256":"7751fe3d63cb9b68f15c7a7e85ecae2a6b306364e08789b03245126455a76107"},"schema_version":"1.0","source":{"id":"2606.10753","kind":"arxiv","version":1}},"canonical_sha256":"b9d6148c22e5c8413b93d9f5f432abeca7aade52b4bc8e9fcadf5c5077fe8f6d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b9d6148c22e5c8413b93d9f5f432abeca7aade52b4bc8e9fcadf5c5077fe8f6d","first_computed_at":"2026-06-10T01:10:38.544270Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-10T01:10:38.544270Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vKaFoLaefa6vCZrsQBY151PouGm/T/gXHfI71aDYNqvyI2f4Vabf2b4z+zFAc9qowDpFQFxs9x2TicLWbDszBw==","signature_status":"signed_v1","signed_at":"2026-06-10T01:10:38.545146Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.10753","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2cd7143fb174b21eb3c3c415d320d31196bfc0f1d639acd71b1686465ca9c4b7","sha256:02575de55c36e6806463b08dd06ac46e9e552ad3250e9f3dc3ded7ebfd0fcaa7"],"state_sha256":"c126f5042873c52571ad8ef0e08c0e642e5137be82e6a0549b165e5f68463a81"}