{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:A2H6JS5PZZ5L37GJBA75TBHWCI","short_pith_number":"pith:A2H6JS5P","schema_version":"1.0","canonical_sha256":"068fe4cbafce7abdfcc9083fd984f612091aa4c38c43d76e0910e6401ce917c9","source":{"kind":"arxiv","id":"2212.02126","version":1},"attestation_state":"computed","paper":{"title":"Accelerating Interactive Human-like Manipulation Learning with GPU-based Simulation and High-quality Demonstrations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Kara Moraw, Malte Mosbach, Sven Behnke","submitted_at":"2022-12-05T09:37:27Z","abstract_excerpt":"Dexterous manipulation with anthropomorphic robot hands remains a challenging problem in robotics because of the high-dimensional state and action spaces and complex contacts. Nevertheless, skillful closed-loop manipulation is required to enable humanoid robots to operate in unstructured real-world environments. Reinforcement learning (RL) has traditionally imposed enormous interaction data requirements for optimizing such complex control problems. We introduce a new framework that leverages recent advances in GPU-based simulation along with the strength of imitation learning in guiding policy"},"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":"2212.02126","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2022-12-05T09:37:27Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"1642a1b106f1801dbbfde150e665323751b837d64cb82b3d8955d72d898de1ac","abstract_canon_sha256":"5c65e4b902c7d4beae8cb85a033702e910dce31b3203e8f87d5c4c33cf4cee57"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:22:20.755268Z","signature_b64":"bj6jVx79xJDsaq/SNT7AeanmdWNby35cq/dbOWWWy4I/8iZ9DuXTaTijkZ0Kzao49gG4fw3ZQe9WPvsNthmyCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"068fe4cbafce7abdfcc9083fd984f612091aa4c38c43d76e0910e6401ce917c9","last_reissued_at":"2026-07-05T05:22:20.754788Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:22:20.754788Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Accelerating Interactive Human-like Manipulation Learning with GPU-based Simulation and High-quality Demonstrations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.RO","authors_text":"Kara Moraw, Malte Mosbach, Sven Behnke","submitted_at":"2022-12-05T09:37:27Z","abstract_excerpt":"Dexterous manipulation with anthropomorphic robot hands remains a challenging problem in robotics because of the high-dimensional state and action spaces and complex contacts. Nevertheless, skillful closed-loop manipulation is required to enable humanoid robots to operate in unstructured real-world environments. Reinforcement learning (RL) has traditionally imposed enormous interaction data requirements for optimizing such complex control problems. We introduce a new framework that leverages recent advances in GPU-based simulation along with the strength of imitation learning in guiding policy"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2212.02126","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/2212.02126/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":"2212.02126","created_at":"2026-07-05T05:22:20.754843+00:00"},{"alias_kind":"arxiv_version","alias_value":"2212.02126v1","created_at":"2026-07-05T05:22:20.754843+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2212.02126","created_at":"2026-07-05T05:22:20.754843+00:00"},{"alias_kind":"pith_short_12","alias_value":"A2H6JS5PZZ5L","created_at":"2026-07-05T05:22:20.754843+00:00"},{"alias_kind":"pith_short_16","alias_value":"A2H6JS5PZZ5L37GJ","created_at":"2026-07-05T05:22:20.754843+00:00"},{"alias_kind":"pith_short_8","alias_value":"A2H6JS5P","created_at":"2026-07-05T05:22:20.754843+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/A2H6JS5PZZ5L37GJBA75TBHWCI","json":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI.json","graph_json":"https://pith.science/api/pith-number/A2H6JS5PZZ5L37GJBA75TBHWCI/graph.json","events_json":"https://pith.science/api/pith-number/A2H6JS5PZZ5L37GJBA75TBHWCI/events.json","paper":"https://pith.science/paper/A2H6JS5P"},"agent_actions":{"view_html":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI","download_json":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI.json","view_paper":"https://pith.science/paper/A2H6JS5P","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2212.02126&json=true","fetch_graph":"https://pith.science/api/pith-number/A2H6JS5PZZ5L37GJBA75TBHWCI/graph.json","fetch_events":"https://pith.science/api/pith-number/A2H6JS5PZZ5L37GJBA75TBHWCI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI/action/storage_attestation","attest_author":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI/action/author_attestation","sign_citation":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI/action/citation_signature","submit_replication":"https://pith.science/pith/A2H6JS5PZZ5L37GJBA75TBHWCI/action/replication_record"}},"created_at":"2026-07-05T05:22:20.754843+00:00","updated_at":"2026-07-05T05:22:20.754843+00:00"}