{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:JGKQA2GJQOMQOBVA73QX7NIQOF","short_pith_number":"pith:JGKQA2GJ","schema_version":"1.0","canonical_sha256":"49950068c983990706a0fee17fb510716350ff9dbc8c20be51e13e4692ca1d51","source":{"kind":"arxiv","id":"2503.14408","version":1},"attestation_state":"computed","paper":{"title":"Large Language Models for Virtual Human Gesture Selection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.HC","authors_text":"Ari Shapiro, Laura B. Hensel, Parisa Ghanad Torshizi, Stacy C. Marsella","submitted_at":"2025-03-18T16:49:56Z","abstract_excerpt":"Co-speech gestures convey a wide variety of meanings and play an important role in face-to-face human interactions. These gestures significantly influence the addressee's engagement, recall, comprehension, and attitudes toward the speaker. Similarly, they impact interactions between humans and embodied virtual agents. The process of selecting and animating meaningful gestures has thus become a key focus in the design of these agents. However, automating this gesture selection process poses a significant challenge. Prior gesture generation techniques have varied from fully automated, data-drive"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2503.14408","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.HC","submitted_at":"2025-03-18T16:49:56Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"b4af443667f1e2154da576362f483c59811a44f7411e7053226bdb4f5fb4c3c7","abstract_canon_sha256":"f86200937094360cfb2ae290ad6084d3c3f777eceb83db9a6ea8b329a5603fac"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:34:01.570983Z","signature_b64":"Ulg001Ke5VWeFc12FcLj6UTh7B6XyZCxu3GEpUCyOXvEMjqwbB1e5S7qX7Jrbg9P3upu+yxALiIJJNxZvZbdDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"49950068c983990706a0fee17fb510716350ff9dbc8c20be51e13e4692ca1d51","last_reissued_at":"2026-07-05T10:34:01.570134Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:34:01.570134Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Large Language Models for Virtual Human Gesture Selection","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.HC","authors_text":"Ari Shapiro, Laura B. Hensel, Parisa Ghanad Torshizi, Stacy C. Marsella","submitted_at":"2025-03-18T16:49:56Z","abstract_excerpt":"Co-speech gestures convey a wide variety of meanings and play an important role in face-to-face human interactions. These gestures significantly influence the addressee's engagement, recall, comprehension, and attitudes toward the speaker. Similarly, they impact interactions between humans and embodied virtual agents. The process of selecting and animating meaningful gestures has thus become a key focus in the design of these agents. However, automating this gesture selection process poses a significant challenge. Prior gesture generation techniques have varied from fully automated, data-drive"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.14408","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/2503.14408/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2503.14408","created_at":"2026-07-05T10:34:01.570253+00:00"},{"alias_kind":"arxiv_version","alias_value":"2503.14408v1","created_at":"2026-07-05T10:34:01.570253+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.14408","created_at":"2026-07-05T10:34:01.570253+00:00"},{"alias_kind":"pith_short_12","alias_value":"JGKQA2GJQOMQ","created_at":"2026-07-05T10:34:01.570253+00:00"},{"alias_kind":"pith_short_16","alias_value":"JGKQA2GJQOMQOBVA","created_at":"2026-07-05T10:34:01.570253+00:00"},{"alias_kind":"pith_short_8","alias_value":"JGKQA2GJ","created_at":"2026-07-05T10:34:01.570253+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2508.21087","citing_title":"Can LLMs Generate Behaviors for Embodied Virtual Agents Based on Personality Traits?","ref_index":18,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF","json":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF.json","graph_json":"https://pith.science/api/pith-number/JGKQA2GJQOMQOBVA73QX7NIQOF/graph.json","events_json":"https://pith.science/api/pith-number/JGKQA2GJQOMQOBVA73QX7NIQOF/events.json","paper":"https://pith.science/paper/JGKQA2GJ"},"agent_actions":{"view_html":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF","download_json":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF.json","view_paper":"https://pith.science/paper/JGKQA2GJ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2503.14408&json=true","fetch_graph":"https://pith.science/api/pith-number/JGKQA2GJQOMQOBVA73QX7NIQOF/graph.json","fetch_events":"https://pith.science/api/pith-number/JGKQA2GJQOMQOBVA73QX7NIQOF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF/action/storage_attestation","attest_author":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF/action/author_attestation","sign_citation":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF/action/citation_signature","submit_replication":"https://pith.science/pith/JGKQA2GJQOMQOBVA73QX7NIQOF/action/replication_record"}},"created_at":"2026-07-05T10:34:01.570253+00:00","updated_at":"2026-07-05T10:34:01.570253+00:00"}