{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QPYO4P72NM6PX26JDNIBWGZIDK","short_pith_number":"pith:QPYO4P72","canonical_record":{"source":{"id":"2503.03081","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-05T00:44:12Z","cross_cats_sorted":[],"title_canon_sha256":"3210c5a903dc5a570db2a2c72bee76e074e3dc305456fadc67df8683194970d8","abstract_canon_sha256":"f74a56cda96bea00a662ffbd262f94f0131f3702d2ad8b3246afc108c273b4fa"},"schema_version":"1.0"},"canonical_sha256":"83f0ee3ffa6b3cfbebc91b501b1b281a8c177fa0e5fe690e8744470b0da21f5e","source":{"kind":"arxiv","id":"2503.03081","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.03081","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"arxiv_version","alias_value":"2503.03081v3","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.03081","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_12","alias_value":"QPYO4P72NM6P","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_16","alias_value":"QPYO4P72NM6PX26J","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_8","alias_value":"QPYO4P72","created_at":"2026-07-05T11:58:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QPYO4P72NM6PX26JDNIBWGZIDK","target":"record","payload":{"canonical_record":{"source":{"id":"2503.03081","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-05T00:44:12Z","cross_cats_sorted":[],"title_canon_sha256":"3210c5a903dc5a570db2a2c72bee76e074e3dc305456fadc67df8683194970d8","abstract_canon_sha256":"f74a56cda96bea00a662ffbd262f94f0131f3702d2ad8b3246afc108c273b4fa"},"schema_version":"1.0"},"canonical_sha256":"83f0ee3ffa6b3cfbebc91b501b1b281a8c177fa0e5fe690e8744470b0da21f5e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:58:25.670729Z","signature_b64":"v2tLDBk1waiYm38hJ0iJhg3xiqz7u0hVUm8raHRG+nDTdUDe27sPE8TJy9Z+ggepEKXvbLChIeTFzF/TX5DhDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83f0ee3ffa6b3cfbebc91b501b1b281a8c177fa0e5fe690e8744470b0da21f5e","last_reissued_at":"2026-07-05T11:58:25.670223Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:58:25.670223Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2503.03081","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:58:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oIhGlcsa3LL6ESVTiDqZe5osAjqSj4SR92HaUprmxYmpkvxk3//5KTj7nS6E7PbXLfilqV6UKe4gW64gar8lDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:13:30.584185Z"},"content_sha256":"543655e1801dee5e891f84102c054c41c65b24257a91314d35f21b05484d5169","schema_version":"1.0","event_id":"sha256:543655e1801dee5e891f84102c054c41c65b24257a91314d35f21b05484d5169"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QPYO4P72NM6PX26JDNIBWGZIDK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.RO","authors_text":"Cewu Lu, Chenxi Wang, Hao-Shu Fang, Hongjie Fang, Jingjing Chen, Jun Lv, Lixin Yang, Shangning Xia, Weiming Wang, Xinyu Zhan, Xiyan Yi, Yiming Wang, Yunhan Guo, Zihao He","submitted_at":"2025-03-05T00:44:12Z","abstract_excerpt":"Scaling up robotic imitation learning for real-world applications requires efficient and scalable demonstration collection methods. While teleoperation is effective, it depends on costly and inflexible robot platforms. In-the-wild demonstrations offer a promising alternative, but existing collection devices have key limitations: handheld setups offer limited observational coverage, and whole-body systems often require fine-tuning with robot data due to domain gaps. To address these challenges, we present AirExo-2, a low-cost exoskeleton system for large-scale in-the-wild data collection, along"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.03081","kind":"arxiv","version":3},"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/2503.03081/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":"2026-07-05T11:58:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M6j5Hp8xtxMLpRm14ifWnEI9inQf4oa+w5X6P1llnZYw3fARjVGD2oOoff+yQJjdG0DGrW8iM6JBuXTQO+HfBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T11:13:30.585133Z"},"content_sha256":"14491d6836c9b9b09303481658d2eaaaf249b793a4e8f1654764ca2fe940df07","schema_version":"1.0","event_id":"sha256:14491d6836c9b9b09303481658d2eaaaf249b793a4e8f1654764ca2fe940df07"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QPYO4P72NM6PX26JDNIBWGZIDK/bundle.json","state_url":"https://pith.science/pith/QPYO4P72NM6PX26JDNIBWGZIDK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QPYO4P72NM6PX26JDNIBWGZIDK/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":"2026-08-04T11:13:30Z","links":{"resolver":"https://pith.science/pith/QPYO4P72NM6PX26JDNIBWGZIDK","bundle":"https://pith.science/pith/QPYO4P72NM6PX26JDNIBWGZIDK/bundle.json","state":"https://pith.science/pith/QPYO4P72NM6PX26JDNIBWGZIDK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QPYO4P72NM6PX26JDNIBWGZIDK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QPYO4P72NM6PX26JDNIBWGZIDK","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":"f74a56cda96bea00a662ffbd262f94f0131f3702d2ad8b3246afc108c273b4fa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-05T00:44:12Z","title_canon_sha256":"3210c5a903dc5a570db2a2c72bee76e074e3dc305456fadc67df8683194970d8"},"schema_version":"1.0","source":{"id":"2503.03081","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.03081","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"arxiv_version","alias_value":"2503.03081v3","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.03081","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_12","alias_value":"QPYO4P72NM6P","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_16","alias_value":"QPYO4P72NM6PX26J","created_at":"2026-07-05T11:58:25Z"},{"alias_kind":"pith_short_8","alias_value":"QPYO4P72","created_at":"2026-07-05T11:58:25Z"}],"graph_snapshots":[{"event_id":"sha256:14491d6836c9b9b09303481658d2eaaaf249b793a4e8f1654764ca2fe940df07","target":"graph","created_at":"2026-07-05T11:58:25Z","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/2503.03081/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Scaling up robotic imitation learning for real-world applications requires efficient and scalable demonstration collection methods. While teleoperation is effective, it depends on costly and inflexible robot platforms. In-the-wild demonstrations offer a promising alternative, but existing collection devices have key limitations: handheld setups offer limited observational coverage, and whole-body systems often require fine-tuning with robot data due to domain gaps. To address these challenges, we present AirExo-2, a low-cost exoskeleton system for large-scale in-the-wild data collection, along","authors_text":"Cewu Lu, Chenxi Wang, Hao-Shu Fang, Hongjie Fang, Jingjing Chen, Jun Lv, Lixin Yang, Shangning Xia, Weiming Wang, Xinyu Zhan, Xiyan Yi, Yiming Wang, Yunhan Guo, Zihao He","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-05T00:44:12Z","title":"AirExo-2: Scaling up Generalizable Robotic Imitation Learning with Low-Cost Exoskeletons"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.03081","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":"sha256:543655e1801dee5e891f84102c054c41c65b24257a91314d35f21b05484d5169","target":"record","created_at":"2026-07-05T11:58:25Z","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":"f74a56cda96bea00a662ffbd262f94f0131f3702d2ad8b3246afc108c273b4fa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.RO","submitted_at":"2025-03-05T00:44:12Z","title_canon_sha256":"3210c5a903dc5a570db2a2c72bee76e074e3dc305456fadc67df8683194970d8"},"schema_version":"1.0","source":{"id":"2503.03081","kind":"arxiv","version":3}},"canonical_sha256":"83f0ee3ffa6b3cfbebc91b501b1b281a8c177fa0e5fe690e8744470b0da21f5e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83f0ee3ffa6b3cfbebc91b501b1b281a8c177fa0e5fe690e8744470b0da21f5e","first_computed_at":"2026-07-05T11:58:25.670223Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:58:25.670223Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"v2tLDBk1waiYm38hJ0iJhg3xiqz7u0hVUm8raHRG+nDTdUDe27sPE8TJy9Z+ggepEKXvbLChIeTFzF/TX5DhDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:58:25.670729Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.03081","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:543655e1801dee5e891f84102c054c41c65b24257a91314d35f21b05484d5169","sha256:14491d6836c9b9b09303481658d2eaaaf249b793a4e8f1654764ca2fe940df07"],"state_sha256":"10d02427c1c0ffd20f18e0434e8b79d24243d3d8747660ac695c8f0dde192a05"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mn1blzTL+Vyh+aaGbpMBsVMaoJujy3ua/Kpaz85ukLxEf7xK07u9zAhvXAONPWc5XYNhnawso08fXCAtLRsOCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T11:13:30.589658Z","bundle_sha256":"67fbdd2bafe799a368ce3e295baf77b9175e817688e3497a6a46fc3a50469e93"}}