{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:WXTYIVFTL7CGSLDKB4XLHA27RH","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":"ee3fef4fc0ba915f979d81f39ecd5065b280f9cb226b7b04ea9878a67fcb762c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-07T06:37:05Z","title_canon_sha256":"b12315d3f0881237d66e101fbc3c274dff299ce8b6a95a2b097374c7c57c232e"},"schema_version":"1.0","source":{"id":"2502.04692","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.04692","created_at":"2026-07-05T10:13:08Z"},{"alias_kind":"arxiv_version","alias_value":"2502.04692v3","created_at":"2026-07-05T10:13:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.04692","created_at":"2026-07-05T10:13:08Z"},{"alias_kind":"pith_short_12","alias_value":"WXTYIVFTL7CG","created_at":"2026-07-05T10:13:08Z"},{"alias_kind":"pith_short_16","alias_value":"WXTYIVFTL7CGSLDK","created_at":"2026-07-05T10:13:08Z"},{"alias_kind":"pith_short_8","alias_value":"WXTYIVFT","created_at":"2026-07-05T10:13:08Z"}],"graph_snapshots":[{"event_id":"sha256:60d6921a219168bf45c4b72316e7da46e995903916b7af5f41cd361d8cc3a649","target":"graph","created_at":"2026-07-05T10:13:08Z","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/2502.04692/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Humanoid robotics presents significant challenges in artificial intelligence, requiring precise coordination and control of high-degree-of-freedom systems. Designing effective reward functions for deep reinforcement learning (DRL) in this domain remains a critical bottleneck, demanding extensive manual effort, domain expertise, and iterative refinement. To overcome these challenges, we introduce STRIDE, a novel framework built on agentic engineering to automate reward design, DRL training, and feedback optimization for humanoid robot locomotion tasks. By combining the structured principles of ","authors_text":"Jinxiong Lu, Luhui Hu, Yueting Zhuang, Yunxin Liu, Yuxiao Chen, Zhenwei Wu","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-07T06:37:05Z","title":"STRIDE: Automating Reward Design, Deep Reinforcement Learning Training and Feedback Optimization in Humanoid Robotics Locomotion"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.04692","kind":"arxiv","version":3},"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:aed1ab8c3fa3e7bc4467fd5dc79330bed02c455e64c25f58754e82bf7e3b63b0","target":"record","created_at":"2026-07-05T10:13:08Z","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":"ee3fef4fc0ba915f979d81f39ecd5065b280f9cb226b7b04ea9878a67fcb762c","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2025-02-07T06:37:05Z","title_canon_sha256":"b12315d3f0881237d66e101fbc3c274dff299ce8b6a95a2b097374c7c57c232e"},"schema_version":"1.0","source":{"id":"2502.04692","kind":"arxiv","version":3}},"canonical_sha256":"b5e78454b35fc4692c6a0f2eb3835f89dba0edcd9de6a5e42fb543e973606a61","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b5e78454b35fc4692c6a0f2eb3835f89dba0edcd9de6a5e42fb543e973606a61","first_computed_at":"2026-07-05T10:13:08.446016Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:13:08.446016Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"PM+p5JpQ3kXIb8bo/qNckXw+XrsvXLU9n2EF6UoKQZleKsBql8M5iN6X2E7l5DvrSwWFllo3hNssVxkJE8ZmCw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:13:08.446572Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.04692","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:aed1ab8c3fa3e7bc4467fd5dc79330bed02c455e64c25f58754e82bf7e3b63b0","sha256:60d6921a219168bf45c4b72316e7da46e995903916b7af5f41cd361d8cc3a649"],"state_sha256":"faad95ed031d66db903f8f19ca2ac56af208e00149ab3a71070c49afd20f792d"}