{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:RF2V4OPJFJDVKMHL4VPY7R43XM","short_pith_number":"pith:RF2V4OPJ","canonical_record":{"source":{"id":"2503.16197","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-20T14:44:45Z","cross_cats_sorted":[],"title_canon_sha256":"539b4d3ad1b241c1af81ac1fcaba8fbec2e65ffcbd5b572cc5795914aa2821bf","abstract_canon_sha256":"c8efb6b3b592c45ec7e732c2554adfd0dde8a8ca74b06f11986ad12e4021363a"},"schema_version":"1.0"},"canonical_sha256":"89755e39e92a475530ebe55f8fc79bbb0740f9c7e1b8b086feefc44618906466","source":{"kind":"arxiv","id":"2503.16197","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.16197","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"arxiv_version","alias_value":"2503.16197v2","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.16197","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_12","alias_value":"RF2V4OPJFJDV","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_16","alias_value":"RF2V4OPJFJDVKMHL","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_8","alias_value":"RF2V4OPJ","created_at":"2026-07-05T11:59:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:RF2V4OPJFJDVKMHL4VPY7R43XM","target":"record","payload":{"canonical_record":{"source":{"id":"2503.16197","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-20T14:44:45Z","cross_cats_sorted":[],"title_canon_sha256":"539b4d3ad1b241c1af81ac1fcaba8fbec2e65ffcbd5b572cc5795914aa2821bf","abstract_canon_sha256":"c8efb6b3b592c45ec7e732c2554adfd0dde8a8ca74b06f11986ad12e4021363a"},"schema_version":"1.0"},"canonical_sha256":"89755e39e92a475530ebe55f8fc79bbb0740f9c7e1b8b086feefc44618906466","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:59:41.064972Z","signature_b64":"RG3w3fyCcU9kidCRypzUSbtuHgMopidFkmTvM37wIbXO84RqFSZfd2g/GWN29Qsk7ouNumNr9pn9Anz9JxrdAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"89755e39e92a475530ebe55f8fc79bbb0740f9c7e1b8b086feefc44618906466","last_reissued_at":"2026-07-05T11:59:41.064469Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:59:41.064469Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.16197","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:59:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9z/7zVl4G21XMgUAhQGhP1sPN5pV34touLLHPdSptaqGRuvVPm9jFqIsbiL45ok/3Mi3KfHW6fw+Mg+sYboPCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:50:51.804594Z"},"content_sha256":"a8dfb989bd976240fe77271d52c2423ce60aa5b60bb72d1b86c07fc1dfac6068","schema_version":"1.0","event_id":"sha256:a8dfb989bd976240fe77271d52c2423ce60aa5b60bb72d1b86c07fc1dfac6068"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:RF2V4OPJFJDVKMHL4VPY7R43XM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cosimo Della Santina, Georgios Apostolides, Jens Kober, Jiatao Ding, Wei Pan","submitted_at":"2025-03-20T14:44:45Z","abstract_excerpt":"Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this challenge via imitation-based deep reinforcement learning with a progressive training process. To start, we learn the jumping skill by mimicking a coarse jumping example generated by model-based trajectory optimization. Subsequently, we generalize the learned policy to broader situations, including various distances in both forward and lateral directions, and then pursue robust jumping in unknown ground unevenness. In"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.16197","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/2503.16197/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:59:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4IkOxhdRoLiZnNvjtHKr4XnMxfLYUANJjGIyXBnusd+H+hy9iBwdJU3x5usLRJbD8eqhen8WKS9ODDyyAcyzCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T11:50:51.804978Z"},"content_sha256":"95d6ce9c385b4037dd5c37144c9ff83988229910bc328ff3762bc6bbf3b6473d","schema_version":"1.0","event_id":"sha256:95d6ce9c385b4037dd5c37144c9ff83988229910bc328ff3762bc6bbf3b6473d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/bundle.json","state_url":"https://pith.science/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-19T11:50:51Z","links":{"resolver":"https://pith.science/pith/RF2V4OPJFJDVKMHL4VPY7R43XM","bundle":"https://pith.science/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/bundle.json","state":"https://pith.science/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RF2V4OPJFJDVKMHL4VPY7R43XM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:RF2V4OPJFJDVKMHL4VPY7R43XM","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":"c8efb6b3b592c45ec7e732c2554adfd0dde8a8ca74b06f11986ad12e4021363a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-20T14:44:45Z","title_canon_sha256":"539b4d3ad1b241c1af81ac1fcaba8fbec2e65ffcbd5b572cc5795914aa2821bf"},"schema_version":"1.0","source":{"id":"2503.16197","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.16197","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"arxiv_version","alias_value":"2503.16197v2","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.16197","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_12","alias_value":"RF2V4OPJFJDV","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_16","alias_value":"RF2V4OPJFJDVKMHL","created_at":"2026-07-05T11:59:41Z"},{"alias_kind":"pith_short_8","alias_value":"RF2V4OPJ","created_at":"2026-07-05T11:59:41Z"}],"graph_snapshots":[{"event_id":"sha256:95d6ce9c385b4037dd5c37144c9ff83988229910bc328ff3762bc6bbf3b6473d","target":"graph","created_at":"2026-07-05T11:59:41Z","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/2503.16197/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Achieving controlled jumping behaviour for a quadruped robot is a challenging task, especially when introducing passive compliance in mechanical design. This study addresses this challenge via imitation-based deep reinforcement learning with a progressive training process. To start, we learn the jumping skill by mimicking a coarse jumping example generated by model-based trajectory optimization. Subsequently, we generalize the learned policy to broader situations, including various distances in both forward and lateral directions, and then pursue robust jumping in unknown ground unevenness. In","authors_text":"Cosimo Della Santina, Georgios Apostolides, Jens Kober, Jiatao Ding, Wei Pan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-20T14:44:45Z","title":"Explosive Jumping with Rigid and Articulated Soft Quadrupeds via Example Guided Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.16197","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:a8dfb989bd976240fe77271d52c2423ce60aa5b60bb72d1b86c07fc1dfac6068","target":"record","created_at":"2026-07-05T11:59:41Z","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":"c8efb6b3b592c45ec7e732c2554adfd0dde8a8ca74b06f11986ad12e4021363a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-20T14:44:45Z","title_canon_sha256":"539b4d3ad1b241c1af81ac1fcaba8fbec2e65ffcbd5b572cc5795914aa2821bf"},"schema_version":"1.0","source":{"id":"2503.16197","kind":"arxiv","version":2}},"canonical_sha256":"89755e39e92a475530ebe55f8fc79bbb0740f9c7e1b8b086feefc44618906466","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"89755e39e92a475530ebe55f8fc79bbb0740f9c7e1b8b086feefc44618906466","first_computed_at":"2026-07-05T11:59:41.064469Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:59:41.064469Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"RG3w3fyCcU9kidCRypzUSbtuHgMopidFkmTvM37wIbXO84RqFSZfd2g/GWN29Qsk7ouNumNr9pn9Anz9JxrdAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:59:41.064972Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.16197","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a8dfb989bd976240fe77271d52c2423ce60aa5b60bb72d1b86c07fc1dfac6068","sha256:95d6ce9c385b4037dd5c37144c9ff83988229910bc328ff3762bc6bbf3b6473d"],"state_sha256":"36bf984c65c1f66a22850135478b96ee590a381cb8d18db7adaf8a8245d799bc"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D7AVnihbAwmwZ/1Pspobh3mEyv8QWjFU+PIJOtyYbn+ITREflb8hIM384YlkzWcFu4sNX0tergMp8nbzQZHHBg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T11:50:51.807314Z","bundle_sha256":"5ee3f4f14eb9cc7ccc748eb706d0eb51165e90caa1ed441cb43818de9543e16b"}}