{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GTXQQYO7TJWGHCNATTJ57S774D","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":"1b9ab6461a6d640ee271dc8aafe502902e47ff126d492d78d79c4fa3c00e096b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-27T13:03:08Z","title_canon_sha256":"a8a07bac55e4206c2c9bdfcb25b920868ec1acf5615c28a7a59bcd99b5898c16"},"schema_version":"1.0","source":{"id":"2502.20061","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.20061","created_at":"2026-07-05T10:21:31Z"},{"alias_kind":"arxiv_version","alias_value":"2502.20061v2","created_at":"2026-07-05T10:21:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.20061","created_at":"2026-07-05T10:21:31Z"},{"alias_kind":"pith_short_12","alias_value":"GTXQQYO7TJWG","created_at":"2026-07-05T10:21:31Z"},{"alias_kind":"pith_short_16","alias_value":"GTXQQYO7TJWGHCNA","created_at":"2026-07-05T10:21:31Z"},{"alias_kind":"pith_short_8","alias_value":"GTXQQYO7","created_at":"2026-07-05T10:21:31Z"}],"graph_snapshots":[{"event_id":"sha256:5b5d02114eda36b377415b01eb48155a577acf9db56eae607f503f00060c9bbb","target":"graph","created_at":"2026-07-05T10:21:31Z","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/2502.20061/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Humanoid robots encounter considerable difficulties in autonomously recovering from falls, especially within dynamic and unstructured environments. Conventional control methodologies are often inadequate in addressing the complexities associated with high-dimensional dynamics and the contact-rich nature of fall recovery. Meanwhile, reinforcement learning techniques are hindered by issues related to sparse rewards, intricate collision scenarios, and discrepancies between simulation and real-world applications. In this study, we introduce a multi-stage curriculum learning framework, termed HiFAR","authors_text":"Changsheng Luo, Mingguo Zhao, Penghui Chen, Wenhan Cai, Yushi Wang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-27T13:03:08Z","title":"HiFAR: Multi-Stage Curriculum Learning for High-Dynamics Humanoid Fall Recovery"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.20061","kind":"arxiv","version":2},"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":"sha256:4928b191714b32d311bd7f1e1982e054be953c2db0e23ecad8e85bb06ee08bc2","target":"record","created_at":"2026-07-05T10:21:31Z","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":"1b9ab6461a6d640ee271dc8aafe502902e47ff126d492d78d79c4fa3c00e096b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-27T13:03:08Z","title_canon_sha256":"a8a07bac55e4206c2c9bdfcb25b920868ec1acf5615c28a7a59bcd99b5898c16"},"schema_version":"1.0","source":{"id":"2502.20061","kind":"arxiv","version":2}},"canonical_sha256":"34ef0861df9a6c6389a09cd3dfcbffe0d0afcf7ce8d27fd7653f64e2d4f6a8ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"34ef0861df9a6c6389a09cd3dfcbffe0d0afcf7ce8d27fd7653f64e2d4f6a8ff","first_computed_at":"2026-07-05T10:21:31.983418Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:21:31.983418Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Vm8dN/XlqbMfgqXuF2ReFix02GkPNlDs3ZUqR5ZC7ETf57hjljmKPTKXh2ONlM48u5u3Yeizq0TlmLp+RHB+CQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:21:31.983947Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.20061","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4928b191714b32d311bd7f1e1982e054be953c2db0e23ecad8e85bb06ee08bc2","sha256:5b5d02114eda36b377415b01eb48155a577acf9db56eae607f503f00060c9bbb"],"state_sha256":"2e0880fa6f5350e5a7b573ddd712ba26b7071ea672a6dcfd6dd5938a1c86b93a"}