{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:QD34RFVRFO3ANSECXHFB7PHD4Q","short_pith_number":"pith:QD34RFVR","schema_version":"1.0","canonical_sha256":"80f7c896b12bb606c882b9ca1fbce3e400916cc4d1e86cf864c12443c05f873c","source":{"kind":"arxiv","id":"2307.04619","version":2},"attestation_state":"computed","paper":{"title":"Learning Fine Pinch-Grasp Skills using Tactile Sensing from A Few Real-world Demonstrations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Efi Psomopoulou, Mohammadreza Kasaei, Nathan F. Lepora, Ruoshi Wen, Wanming Yu, Xiaofeng Mao, Yucheng Xu, Zhibin Li","submitted_at":"2023-07-10T15:07:29Z","abstract_excerpt":"Imitation learning for robot dexterous manipulation, especially with a real robot setup, typically requires a large number of demonstrations. In this paper, we present a data-efficient learning from demonstration framework which exploits the use of rich tactile sensing data and achieves fine bimanual pinch grasping. Specifically, we employ a convolutional autoencoder network that can effectively extract and encode high-dimensional tactile information. Further, We develop a framework that achieves efficient multi-sensor fusion for imitation learning, allowing the robot to learn contact-aware se"},"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":"2307.04619","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-07-10T15:07:29Z","cross_cats_sorted":[],"title_canon_sha256":"b6d9d8d09b0bef3d392283efdc2b72a2799a4bdac823a1b6b795739daccae9f0","abstract_canon_sha256":"db5d0049b1ee8e4f09cc67bc6f54e9b986633ae32dc96f54283130495ae7faa8"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:50.344024Z","signature_b64":"yqtqfm6kgnjF8GWykc/C5qMdhyx0daiDir4542k+vzXpbo2vlfoykb7WcO384rti9H9YYpxyHi3tUPPy3w8LBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"80f7c896b12bb606c882b9ca1fbce3e400916cc4d1e86cf864c12443c05f873c","last_reissued_at":"2026-07-05T07:56:50.343597Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:50.343597Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Learning Fine Pinch-Grasp Skills using Tactile Sensing from A Few Real-world Demonstrations","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Efi Psomopoulou, Mohammadreza Kasaei, Nathan F. Lepora, Ruoshi Wen, Wanming Yu, Xiaofeng Mao, Yucheng Xu, Zhibin Li","submitted_at":"2023-07-10T15:07:29Z","abstract_excerpt":"Imitation learning for robot dexterous manipulation, especially with a real robot setup, typically requires a large number of demonstrations. In this paper, we present a data-efficient learning from demonstration framework which exploits the use of rich tactile sensing data and achieves fine bimanual pinch grasping. Specifically, we employ a convolutional autoencoder network that can effectively extract and encode high-dimensional tactile information. Further, We develop a framework that achieves efficient multi-sensor fusion for imitation learning, allowing the robot to learn contact-aware se"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2307.04619","kind":"arxiv","version":2},"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/2307.04619/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":"2307.04619","created_at":"2026-07-05T07:56:50.343653+00:00"},{"alias_kind":"arxiv_version","alias_value":"2307.04619v2","created_at":"2026-07-05T07:56:50.343653+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2307.04619","created_at":"2026-07-05T07:56:50.343653+00:00"},{"alias_kind":"pith_short_12","alias_value":"QD34RFVRFO3A","created_at":"2026-07-05T07:56:50.343653+00:00"},{"alias_kind":"pith_short_16","alias_value":"QD34RFVRFO3ANSEC","created_at":"2026-07-05T07:56:50.343653+00:00"},{"alias_kind":"pith_short_8","alias_value":"QD34RFVR","created_at":"2026-07-05T07:56:50.343653+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/QD34RFVRFO3ANSECXHFB7PHD4Q","json":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q.json","graph_json":"https://pith.science/api/pith-number/QD34RFVRFO3ANSECXHFB7PHD4Q/graph.json","events_json":"https://pith.science/api/pith-number/QD34RFVRFO3ANSECXHFB7PHD4Q/events.json","paper":"https://pith.science/paper/QD34RFVR"},"agent_actions":{"view_html":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q","download_json":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q.json","view_paper":"https://pith.science/paper/QD34RFVR","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2307.04619&json=true","fetch_graph":"https://pith.science/api/pith-number/QD34RFVRFO3ANSECXHFB7PHD4Q/graph.json","fetch_events":"https://pith.science/api/pith-number/QD34RFVRFO3ANSECXHFB7PHD4Q/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q/action/storage_attestation","attest_author":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q/action/author_attestation","sign_citation":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q/action/citation_signature","submit_replication":"https://pith.science/pith/QD34RFVRFO3ANSECXHFB7PHD4Q/action/replication_record"}},"created_at":"2026-07-05T07:56:50.343653+00:00","updated_at":"2026-07-05T07:56:50.343653+00:00"}