{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:2YS4IXKLNGWZR5GNTDEMKSJVAN","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":"38898a10c21b2278165fdb209e12514025d96153dc6d364a86891989657af27d","cross_cats_sorted":["cs.CV","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-31T13:34:15Z","title_canon_sha256":"a89734598734657001f061c91149a5c84e219eeba677cda243ae275482e4c2b7"},"schema_version":"1.0","source":{"id":"2507.23544","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.23544","created_at":"2026-07-05T11:46:25Z"},{"alias_kind":"arxiv_version","alias_value":"2507.23544v1","created_at":"2026-07-05T11:46:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.23544","created_at":"2026-07-05T11:46:25Z"},{"alias_kind":"pith_short_12","alias_value":"2YS4IXKLNGWZ","created_at":"2026-07-05T11:46:25Z"},{"alias_kind":"pith_short_16","alias_value":"2YS4IXKLNGWZR5GN","created_at":"2026-07-05T11:46:25Z"},{"alias_kind":"pith_short_8","alias_value":"2YS4IXKL","created_at":"2026-07-05T11:46:25Z"}],"graph_snapshots":[{"event_id":"sha256:6e233f0fc40c9cb7b3db59f86fa3bf96c6334ca5bbcb2aa68989c33bce1672f2","target":"graph","created_at":"2026-07-05T11:46:25Z","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/2507.23544/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, the demand for social robots has grown, requiring them to adapt their behaviors based on users' states. Accurately assessing user experience (UX) in human-robot interaction (HRI) is crucial for achieving this adaptability. UX is a multi-faceted measure encompassing aspects such as sentiment and engagement, yet existing methods often focus on these individually. This study proposes a UX estimation method for HRI by leveraging multimodal social signals. We construct a UX dataset and develop a Transformer-based model that utilizes facial expressions and voice for estimation. Unli","authors_text":"Jun Baba, Junya Nakanishi, Ryo Miyoshi, Takuya Iwamoto, Yuki Okafuji","cross_cats":["cs.CV","cs.HC"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-31T13:34:15Z","title":"User Experience Estimation in Human-Robot Interaction Via Multi-Instance Learning of Multimodal Social Signals"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.23544","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":"sha256:5f594fcc27030f34c7cc6490e476d5f79a9f8dceb036d489e5ddc8295dec1bfa","target":"record","created_at":"2026-07-05T11:46:25Z","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":"38898a10c21b2278165fdb209e12514025d96153dc6d364a86891989657af27d","cross_cats_sorted":["cs.CV","cs.HC"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-07-31T13:34:15Z","title_canon_sha256":"a89734598734657001f061c91149a5c84e219eeba677cda243ae275482e4c2b7"},"schema_version":"1.0","source":{"id":"2507.23544","kind":"arxiv","version":1}},"canonical_sha256":"d625c45d4b69ad98f4cd98c8c54935036cd0f238a98cff536f3150a11c544aa5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d625c45d4b69ad98f4cd98c8c54935036cd0f238a98cff536f3150a11c544aa5","first_computed_at":"2026-07-05T11:46:25.963609Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:25.963609Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QeOrd4qCNKsGKkc+4N/GqjI5sz6eGi3YCvhyQPKQeRyF2x68iJLuiUKpiSr+Yzawn3L038/bK2BVATkQNcW2BQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:25.964116Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.23544","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f594fcc27030f34c7cc6490e476d5f79a9f8dceb036d489e5ddc8295dec1bfa","sha256:6e233f0fc40c9cb7b3db59f86fa3bf96c6334ca5bbcb2aa68989c33bce1672f2"],"state_sha256":"2d96f91ec2f8a6b5240f3373cc27da646751087be94026118248648eb54f80ff"}