{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:JXSFXQNWEF4RDCEGB747FTTLXJ","short_pith_number":"pith:JXSFXQNW","canonical_record":{"source":{"id":"2502.03717","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-06T02:07:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2206df41d30a935f9459248025da685ce2553f55de3d227116040c5008989bf1","abstract_canon_sha256":"906c5231858362428610fb55db5fcf997674ba4c0a2c7550c9070615c02be18e"},"schema_version":"1.0"},"canonical_sha256":"4de45bc1b621791188860ff9f2ce6bba6af1c10c16e5e811dc14be762a197364","source":{"kind":"arxiv","id":"2502.03717","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.03717","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"arxiv_version","alias_value":"2502.03717v2","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03717","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_12","alias_value":"JXSFXQNWEF4R","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_16","alias_value":"JXSFXQNWEF4RDCEG","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_8","alias_value":"JXSFXQNW","created_at":"2026-07-05T10:42:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:JXSFXQNWEF4RDCEGB747FTTLXJ","target":"record","payload":{"canonical_record":{"source":{"id":"2502.03717","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-06T02:07:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"2206df41d30a935f9459248025da685ce2553f55de3d227116040c5008989bf1","abstract_canon_sha256":"906c5231858362428610fb55db5fcf997674ba4c0a2c7550c9070615c02be18e"},"schema_version":"1.0"},"canonical_sha256":"4de45bc1b621791188860ff9f2ce6bba6af1c10c16e5e811dc14be762a197364","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:42:14.924167Z","signature_b64":"AmOcecSIbXAteX63ZYgXgRdYWJSC6pc/FrX1/MPmWcQWNp6kT6I2ygngatt3vjps1ysQUsldVotDPQbSJyTaBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4de45bc1b621791188860ff9f2ce6bba6af1c10c16e5e811dc14be762a197364","last_reissued_at":"2026-07-05T10:42:14.923707Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:42:14.923707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.03717","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":"2026-07-05T10:42:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"n+l1IzTqqC0Qvg8G2C3SwETuW1HOCChivpAqQG6VgbCu94n2OD/k6Mk+SfFSc31G+quM8YYlTgpVFd6/Rs3UBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T22:57:02.086838Z"},"content_sha256":"e4753c06db01e651247ef04b1626da2ea4aff4dd54041d9205cd33ddbb1ba466","schema_version":"1.0","event_id":"sha256:e4753c06db01e651247ef04b1626da2ea4aff4dd54041d9205cd33ddbb1ba466"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:JXSFXQNWEF4RDCEGB747FTTLXJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Dorsa Sadigh, Jaden Clark, Joey Hejna","submitted_at":"2025-02-06T02:07:18Z","abstract_excerpt":"Expressive robotic behavior is essential for the widespread acceptance of robots in social environments. Recent advancements in learned legged locomotion controllers have enabled more dynamic and versatile robot behaviors. However, determining the optimal behavior for interactions with different users across varied scenarios remains a challenge. Current methods either rely on natural language input, which is efficient but low-resolution, or learn from human preferences, which, although high-resolution, is sample inefficient. This paper introduces a novel approach that leverages priors generate"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03717","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/2502.03717/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":"2026-07-05T10:42:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6I1PQPmJta9aK3QGJjuyGwwsylHfr0Z2B5zLALmx5CulOvpWgGalKdS8ihgsThtHZ9tVApXQO3VjmC/ZeQlDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T22:57:02.087715Z"},"content_sha256":"59ed215abfc22893e03ae56754f84534298752e00132fe7f1b3b9d2d1f5b5484","schema_version":"1.0","event_id":"sha256:59ed215abfc22893e03ae56754f84534298752e00132fe7f1b3b9d2d1f5b5484"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/bundle.json","state_url":"https://pith.science/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/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":"2026-08-14T22:57:02Z","links":{"resolver":"https://pith.science/pith/JXSFXQNWEF4RDCEGB747FTTLXJ","bundle":"https://pith.science/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/bundle.json","state":"https://pith.science/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JXSFXQNWEF4RDCEGB747FTTLXJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:JXSFXQNWEF4RDCEGB747FTTLXJ","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":"906c5231858362428610fb55db5fcf997674ba4c0a2c7550c9070615c02be18e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-06T02:07:18Z","title_canon_sha256":"2206df41d30a935f9459248025da685ce2553f55de3d227116040c5008989bf1"},"schema_version":"1.0","source":{"id":"2502.03717","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.03717","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"arxiv_version","alias_value":"2502.03717v2","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.03717","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_12","alias_value":"JXSFXQNWEF4R","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_16","alias_value":"JXSFXQNWEF4RDCEG","created_at":"2026-07-05T10:42:14Z"},{"alias_kind":"pith_short_8","alias_value":"JXSFXQNW","created_at":"2026-07-05T10:42:14Z"}],"graph_snapshots":[{"event_id":"sha256:59ed215abfc22893e03ae56754f84534298752e00132fe7f1b3b9d2d1f5b5484","target":"graph","created_at":"2026-07-05T10:42:14Z","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/2502.03717/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Expressive robotic behavior is essential for the widespread acceptance of robots in social environments. Recent advancements in learned legged locomotion controllers have enabled more dynamic and versatile robot behaviors. However, determining the optimal behavior for interactions with different users across varied scenarios remains a challenge. Current methods either rely on natural language input, which is efficient but low-resolution, or learn from human preferences, which, although high-resolution, is sample inefficient. This paper introduces a novel approach that leverages priors generate","authors_text":"Dorsa Sadigh, Jaden Clark, Joey Hejna","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-06T02:07:18Z","title":"Efficiently Generating Expressive Quadruped Behaviors via Language-Guided Preference Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.03717","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:e4753c06db01e651247ef04b1626da2ea4aff4dd54041d9205cd33ddbb1ba466","target":"record","created_at":"2026-07-05T10:42:14Z","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":"906c5231858362428610fb55db5fcf997674ba4c0a2c7550c9070615c02be18e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2025-02-06T02:07:18Z","title_canon_sha256":"2206df41d30a935f9459248025da685ce2553f55de3d227116040c5008989bf1"},"schema_version":"1.0","source":{"id":"2502.03717","kind":"arxiv","version":2}},"canonical_sha256":"4de45bc1b621791188860ff9f2ce6bba6af1c10c16e5e811dc14be762a197364","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4de45bc1b621791188860ff9f2ce6bba6af1c10c16e5e811dc14be762a197364","first_computed_at":"2026-07-05T10:42:14.923707Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:42:14.923707Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"AmOcecSIbXAteX63ZYgXgRdYWJSC6pc/FrX1/MPmWcQWNp6kT6I2ygngatt3vjps1ysQUsldVotDPQbSJyTaBw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:42:14.924167Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.03717","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e4753c06db01e651247ef04b1626da2ea4aff4dd54041d9205cd33ddbb1ba466","sha256:59ed215abfc22893e03ae56754f84534298752e00132fe7f1b3b9d2d1f5b5484"],"state_sha256":"af0909a47b0bfab817c72f746203d32c50de920d6902042e0718cea1920ca40a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WjyXJXzUDvUFIOA97rihSc4relmVh450uRoZSi7z0enpILMxWDmXJ7YqLkTFXbRHPWWkzLY7YrnnJD6ca6o6CQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T22:57:02.095778Z","bundle_sha256":"91992ccbaa6396dfad2a7e558cc1c4e7941df2377fd4fe4e7489d75ee27db7da"}}