{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:PE42LMYGO6OC27NHLSWJ2LPVMX","short_pith_number":"pith:PE42LMYG","schema_version":"1.0","canonical_sha256":"7939a5b306779c2d7da75cac9d2df565ed59f17f68b1409aeda2618b7a214625","source":{"kind":"arxiv","id":"2411.12711","version":1},"attestation_state":"computed","paper":{"title":"UBSoft: A Simulation Platform for Robotic Skill Learning in Unbounded Soft Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Chuang Gan, Chunru Lin, Jugang Fan, Lixing Fang, Tsun-Hsuan Wang, Yian Wang, Zeyuan Yang, Zhehuan Chen, Zhou Xian","submitted_at":"2024-11-19T18:25:38Z","abstract_excerpt":"It is desired to equip robots with the capability of interacting with various soft materials as they are ubiquitous in the real world. While physics simulations are one of the predominant methods for data collection and robot training, simulating soft materials presents considerable challenges. Specifically, it is significantly more costly than simulating rigid objects in terms of simulation speed and storage requirements. These limitations typically restrict the scope of studies on soft materials to small and bounded areas, thereby hindering the learning of skills in broader spaces. To addres"},"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":"2411.12711","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-11-19T18:25:38Z","cross_cats_sorted":[],"title_canon_sha256":"949c07dbac9b7935c8e95438170af66f469351f9266ae527b562c55bbdad6963","abstract_canon_sha256":"71517eeb8a3b37e4ad75ddee52e20b156ed4d7a9270e420c704621e768e40b41"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:37:47.143766Z","signature_b64":"FShbM+LFn8bOy/b9soLNe4rt7h6muOVkzV6RKvhyYMBKJWwWWDh1PbUZpfyvrXmiZNkLASFWvV891xoIxI0LBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7939a5b306779c2d7da75cac9d2df565ed59f17f68b1409aeda2618b7a214625","last_reissued_at":"2026-07-05T09:37:47.143304Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:37:47.143304Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"UBSoft: A Simulation Platform for Robotic Skill Learning in Unbounded Soft Environments","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Chuang Gan, Chunru Lin, Jugang Fan, Lixing Fang, Tsun-Hsuan Wang, Yian Wang, Zeyuan Yang, Zhehuan Chen, Zhou Xian","submitted_at":"2024-11-19T18:25:38Z","abstract_excerpt":"It is desired to equip robots with the capability of interacting with various soft materials as they are ubiquitous in the real world. While physics simulations are one of the predominant methods for data collection and robot training, simulating soft materials presents considerable challenges. Specifically, it is significantly more costly than simulating rigid objects in terms of simulation speed and storage requirements. These limitations typically restrict the scope of studies on soft materials to small and bounded areas, thereby hindering the learning of skills in broader spaces. To addres"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.12711","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/2411.12711/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":"2411.12711","created_at":"2026-07-05T09:37:47.143371+00:00"},{"alias_kind":"arxiv_version","alias_value":"2411.12711v1","created_at":"2026-07-05T09:37:47.143371+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.12711","created_at":"2026-07-05T09:37:47.143371+00:00"},{"alias_kind":"pith_short_12","alias_value":"PE42LMYGO6OC","created_at":"2026-07-05T09:37:47.143371+00:00"},{"alias_kind":"pith_short_16","alias_value":"PE42LMYGO6OC27NH","created_at":"2026-07-05T09:37:47.143371+00:00"},{"alias_kind":"pith_short_8","alias_value":"PE42LMYG","created_at":"2026-07-05T09:37:47.143371+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.30326","citing_title":"RoboWits: Unexpected Challenges for Robotic Creative Problem Solving","ref_index":26,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX","json":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX.json","graph_json":"https://pith.science/api/pith-number/PE42LMYGO6OC27NHLSWJ2LPVMX/graph.json","events_json":"https://pith.science/api/pith-number/PE42LMYGO6OC27NHLSWJ2LPVMX/events.json","paper":"https://pith.science/paper/PE42LMYG"},"agent_actions":{"view_html":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX","download_json":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX.json","view_paper":"https://pith.science/paper/PE42LMYG","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2411.12711&json=true","fetch_graph":"https://pith.science/api/pith-number/PE42LMYGO6OC27NHLSWJ2LPVMX/graph.json","fetch_events":"https://pith.science/api/pith-number/PE42LMYGO6OC27NHLSWJ2LPVMX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX/action/storage_attestation","attest_author":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX/action/author_attestation","sign_citation":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX/action/citation_signature","submit_replication":"https://pith.science/pith/PE42LMYGO6OC27NHLSWJ2LPVMX/action/replication_record"}},"created_at":"2026-07-05T09:37:47.143371+00:00","updated_at":"2026-07-05T09:37:47.143371+00:00"}