{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:54SN7Z5VEETTEH6R2XWCWOSVEY","short_pith_number":"pith:54SN7Z5V","schema_version":"1.0","canonical_sha256":"ef24dfe7b52127321fd1d5ec2b3a552614032b2db3b7ab1a1769229141e4b630","source":{"kind":"arxiv","id":"2606.08341","version":1},"attestation_state":"computed","paper":{"title":"Uncertainty-Aware Intention Prediction for Human-to-Robot Assembly Teleoperation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Akhil Joshi, Conner Wallace, Fnu Heman, John Dang, Jun Sheng, Kolin Xu, Mingyu Cai, Pinhas Ben-Tzvi, Yixuan Wang","submitted_at":"2026-06-06T21:13:57Z","abstract_excerpt":"In assisted teleoperation for human-robot collaboration, accurate intention prediction is critical for enabling timely and reliable robotic assistance during long-horizon manipulation and assembly tasks. These systems require continuous understanding of user behavior to recognize actions, anticipate intentions, and detect mistakes in real time. However, robot teleoperation demonstrations are costly and hardware-limited, whereas human demonstrations are easier to collect and provide rich temporal structure. To address this challenge, we propose an uncertainty-aware human-to-robot intention pred"},"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":"2606.08341","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-06-06T21:13:57Z","cross_cats_sorted":[],"title_canon_sha256":"79d81eab56f39011c8b6331342fca95e8d3a9fdb88abf141d5f4f1c9d5faae10","abstract_canon_sha256":"bb3296d853ac5dc6309c35f4d7f60c99512eebc998c276edc26872db8c0abbb9"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-09T01:05:34.089307Z","signature_b64":"WM6CYOq9LC6cWjhpdJDAW85PExJx1ktjGgXZ2Scog1Avgj10LTDGnVehTLj6g1J3L/wEFp2RsNzcT+OIuoDNCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef24dfe7b52127321fd1d5ec2b3a552614032b2db3b7ab1a1769229141e4b630","last_reissued_at":"2026-06-09T01:05:34.088900Z","signature_status":"signed_v1","first_computed_at":"2026-06-09T01:05:34.088900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Uncertainty-Aware Intention Prediction for Human-to-Robot Assembly Teleoperation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Akhil Joshi, Conner Wallace, Fnu Heman, John Dang, Jun Sheng, Kolin Xu, Mingyu Cai, Pinhas Ben-Tzvi, Yixuan Wang","submitted_at":"2026-06-06T21:13:57Z","abstract_excerpt":"In assisted teleoperation for human-robot collaboration, accurate intention prediction is critical for enabling timely and reliable robotic assistance during long-horizon manipulation and assembly tasks. These systems require continuous understanding of user behavior to recognize actions, anticipate intentions, and detect mistakes in real time. However, robot teleoperation demonstrations are costly and hardware-limited, whereas human demonstrations are easier to collect and provide rich temporal structure. To address this challenge, we propose an uncertainty-aware human-to-robot intention pred"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.08341","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/2606.08341/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":"2606.08341","created_at":"2026-06-09T01:05:34.088964+00:00"},{"alias_kind":"arxiv_version","alias_value":"2606.08341v1","created_at":"2026-06-09T01:05:34.088964+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.08341","created_at":"2026-06-09T01:05:34.088964+00:00"},{"alias_kind":"pith_short_12","alias_value":"54SN7Z5VEETT","created_at":"2026-06-09T01:05:34.088964+00:00"},{"alias_kind":"pith_short_16","alias_value":"54SN7Z5VEETTEH6R","created_at":"2026-06-09T01:05:34.088964+00:00"},{"alias_kind":"pith_short_8","alias_value":"54SN7Z5V","created_at":"2026-06-09T01:05:34.088964+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY","json":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY.json","graph_json":"https://pith.science/api/pith-number/54SN7Z5VEETTEH6R2XWCWOSVEY/graph.json","events_json":"https://pith.science/api/pith-number/54SN7Z5VEETTEH6R2XWCWOSVEY/events.json","paper":"https://pith.science/paper/54SN7Z5V"},"agent_actions":{"view_html":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY","download_json":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY.json","view_paper":"https://pith.science/paper/54SN7Z5V","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2606.08341&json=true","fetch_graph":"https://pith.science/api/pith-number/54SN7Z5VEETTEH6R2XWCWOSVEY/graph.json","fetch_events":"https://pith.science/api/pith-number/54SN7Z5VEETTEH6R2XWCWOSVEY/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY/action/timestamp_anchor","attest_storage":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY/action/storage_attestation","attest_author":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY/action/author_attestation","sign_citation":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY/action/citation_signature","submit_replication":"https://pith.science/pith/54SN7Z5VEETTEH6R2XWCWOSVEY/action/replication_record"}},"created_at":"2026-06-09T01:05:34.088964+00:00","updated_at":"2026-06-09T01:05:34.088964+00:00"}