{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:GR5OMRB5PEW4HMIKIYPLQ24RVV","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":"23abb3b257b6f6bc51483c794e5ee54ad0ede137534abf99e1f8b358d3a91555","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-29T08:51:38Z","title_canon_sha256":"d8ce927712f28ec1d3bb0ab1b1e96c462adf36b2c907924d961662c6dd52a8a7"},"schema_version":"1.0","source":{"id":"2203.15354","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2203.15354","created_at":"2026-07-05T04:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2203.15354v1","created_at":"2026-07-05T04:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2203.15354","created_at":"2026-07-05T04:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"GR5OMRB5PEW4","created_at":"2026-07-05T04:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"GR5OMRB5PEW4HMIK","created_at":"2026-07-05T04:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"GR5OMRB5","created_at":"2026-07-05T04:09:24Z"}],"graph_snapshots":[{"event_id":"sha256:0dc76285035b2d8439400c00384514ca96cfe5a01da65130db2d19ddbfdad3f2","target":"graph","created_at":"2026-07-05T04:09:24Z","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/2203.15354/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Sign languages are visual languages, with vocabularies as rich as their spoken language counterparts. However, current deep-learning based Sign Language Production (SLP) models produce under-articulated skeleton pose sequences from constrained vocabularies and this limits applicability. To be understandable and accepted by the deaf, an automatic SLP system must be able to generate co-articulated photo-realistic signing sequences for large domains of discourse.\n  In this work, we tackle large-scale SLP by learning to co-articulate between dictionary signs, a method capable of producing smooth s","authors_text":"Ben Saunders, Necati Cihan Camgoz, Richard Bowden","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-29T08:51:38Z","title":"Signing at Scale: Learning to Co-Articulate Signs for Large-Scale Photo-Realistic Sign Language Production"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2203.15354","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":"sha256:70302e25f5b84479319345297cf2670fc06e29b25c8090ce158839152dd72a78","target":"record","created_at":"2026-07-05T04:09:24Z","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":"23abb3b257b6f6bc51483c794e5ee54ad0ede137534abf99e1f8b358d3a91555","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-03-29T08:51:38Z","title_canon_sha256":"d8ce927712f28ec1d3bb0ab1b1e96c462adf36b2c907924d961662c6dd52a8a7"},"schema_version":"1.0","source":{"id":"2203.15354","kind":"arxiv","version":1}},"canonical_sha256":"347ae6443d792dc3b10a461eb86b91ad4ee0d5ba1099b8fadfaa3b4067294b32","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"347ae6443d792dc3b10a461eb86b91ad4ee0d5ba1099b8fadfaa3b4067294b32","first_computed_at":"2026-07-05T04:09:24.461870Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:09:24.461870Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UpmOyO+KCpz8a9ZlHseKm4hFtSH8QTxeECcjKAejEEdMXFm1jEKt+802pHYU3x3K5cdFArzLyvemV+/6ZecdDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:09:24.462261Z","signed_message":"canonical_sha256_bytes"},"source_id":"2203.15354","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:70302e25f5b84479319345297cf2670fc06e29b25c8090ce158839152dd72a78","sha256:0dc76285035b2d8439400c00384514ca96cfe5a01da65130db2d19ddbfdad3f2"],"state_sha256":"acbc6381572fa787e245e8ba832edbd3ec3ac191d8744fecd04689dc67f2bb1d"}