{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:6C7RA3V6MBA737ASCFNLYYQXSD","short_pith_number":"pith:6C7RA3V6","canonical_record":{"source":{"id":"2607.02322","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-02T15:30:26Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"109aa3140239b2a6ac006c42f693b33b608b1bc300c13b4929425791ee9b1bbf","abstract_canon_sha256":"c1226eb6f3bc0cadfcf01bf565f2131dc192cdaa07bf49029244327f2d5ea06e"},"schema_version":"1.0"},"canonical_sha256":"f0bf106ebe6041fdfc12115abc621790f8dfd2de2a178fc87c587b783b8540e6","source":{"kind":"arxiv","id":"2607.02322","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.02322","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"arxiv_version","alias_value":"2607.02322v1","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.02322","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_12","alias_value":"6C7RA3V6MBA7","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_16","alias_value":"6C7RA3V6MBA737AS","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_8","alias_value":"6C7RA3V6","created_at":"2026-07-03T01:17:48Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:6C7RA3V6MBA737ASCFNLYYQXSD","target":"record","payload":{"canonical_record":{"source":{"id":"2607.02322","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-02T15:30:26Z","cross_cats_sorted":["cs.CV"],"title_canon_sha256":"109aa3140239b2a6ac006c42f693b33b608b1bc300c13b4929425791ee9b1bbf","abstract_canon_sha256":"c1226eb6f3bc0cadfcf01bf565f2131dc192cdaa07bf49029244327f2d5ea06e"},"schema_version":"1.0"},"canonical_sha256":"f0bf106ebe6041fdfc12115abc621790f8dfd2de2a178fc87c587b783b8540e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-03T01:17:48.451241Z","signature_b64":"XB0KLrE/G52wZ+5gVHekZ48Lote4ef3bEwbSrw/+sZRNSscyOUOXicBed19tII0lSJzgK0qDFHHSxD3NErELAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0bf106ebe6041fdfc12115abc621790f8dfd2de2a178fc87c587b783b8540e6","last_reissued_at":"2026-07-03T01:17:48.450856Z","signature_status":"signed_v1","first_computed_at":"2026-07-03T01:17:48.450856Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.02322","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-03T01:17:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yEs2BXuuhgHRdWyVCOGFps4prATHdLvCxPjqCxzs82TqoaTJImr2kKOBxh7UWKvVaPPF7lOOoD7hPidnx9oWCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T02:56:19.750894Z"},"content_sha256":"05fa82e1ce0f2ae4f80815b2949eafe3e7a78da50944b0ba141abb7dfa781dfe","schema_version":"1.0","event_id":"sha256:05fa82e1ce0f2ae4f80815b2949eafe3e7a78da50944b0ba141abb7dfa781dfe"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:6C7RA3V6MBA737ASCFNLYYQXSD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"The Moving Eye: Enhancing VLA Spatial Generalization via Hybrid Dynamic Data Collection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CV"],"primary_cat":"cs.RO","authors_text":"Jiang-Jiang Liu, Jiaxing Zhang, Jincheng Tang, Yilong Zhu, Zhengyuan Xie","submitted_at":"2026-07-02T15:30:26Z","abstract_excerpt":"Vision-Language-Action (VLA) models have shown remarkable promise in generalized robotic manipulation. However, their spatial generalization remains fragile. We argue that simply increasing the number of viewpoints is insufficient. Models often fall into the trap of Shortcut Learning, latching onto spurious correlations (e.g., fixed relative poses between objects or between the camera and robot base) rather than learning true spatial relationships. In this work, we propose a data-centric solution to enhance VLA spatial generalization. We utilize a dual-arm setup where one arm performs manipula"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.02322","kind":"arxiv","version":1},"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/2607.02322/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":"2026-07-03T01:17:48Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qTq9w1prmceGvfP/ahfKWtAmAwaf6NgzjIeNfvGnhhNf6IoE7wqoJN3Wik6lEwQZ4lWjTmW8oiqXQ59OaCzRAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-05T02:56:19.751263Z"},"content_sha256":"7d772ec179c66e085146df1061fb05536a07bb17253d2be586ab2c87fcfef1eb","schema_version":"1.0","event_id":"sha256:7d772ec179c66e085146df1061fb05536a07bb17253d2be586ab2c87fcfef1eb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6C7RA3V6MBA737ASCFNLYYQXSD/bundle.json","state_url":"https://pith.science/pith/6C7RA3V6MBA737ASCFNLYYQXSD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6C7RA3V6MBA737ASCFNLYYQXSD/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":"2026-07-05T02:56:19Z","links":{"resolver":"https://pith.science/pith/6C7RA3V6MBA737ASCFNLYYQXSD","bundle":"https://pith.science/pith/6C7RA3V6MBA737ASCFNLYYQXSD/bundle.json","state":"https://pith.science/pith/6C7RA3V6MBA737ASCFNLYYQXSD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6C7RA3V6MBA737ASCFNLYYQXSD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:6C7RA3V6MBA737ASCFNLYYQXSD","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":"c1226eb6f3bc0cadfcf01bf565f2131dc192cdaa07bf49029244327f2d5ea06e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-02T15:30:26Z","title_canon_sha256":"109aa3140239b2a6ac006c42f693b33b608b1bc300c13b4929425791ee9b1bbf"},"schema_version":"1.0","source":{"id":"2607.02322","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.02322","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"arxiv_version","alias_value":"2607.02322v1","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.02322","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_12","alias_value":"6C7RA3V6MBA7","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_16","alias_value":"6C7RA3V6MBA737AS","created_at":"2026-07-03T01:17:48Z"},{"alias_kind":"pith_short_8","alias_value":"6C7RA3V6","created_at":"2026-07-03T01:17:48Z"}],"graph_snapshots":[{"event_id":"sha256:7d772ec179c66e085146df1061fb05536a07bb17253d2be586ab2c87fcfef1eb","target":"graph","created_at":"2026-07-03T01:17:48Z","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/2607.02322/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vision-Language-Action (VLA) models have shown remarkable promise in generalized robotic manipulation. However, their spatial generalization remains fragile. We argue that simply increasing the number of viewpoints is insufficient. Models often fall into the trap of Shortcut Learning, latching onto spurious correlations (e.g., fixed relative poses between objects or between the camera and robot base) rather than learning true spatial relationships. In this work, we propose a data-centric solution to enhance VLA spatial generalization. We utilize a dual-arm setup where one arm performs manipula","authors_text":"Jiang-Jiang Liu, Jiaxing Zhang, Jincheng Tang, Yilong Zhu, Zhengyuan Xie","cross_cats":["cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-02T15:30:26Z","title":"The Moving Eye: Enhancing VLA Spatial Generalization via Hybrid Dynamic Data Collection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.02322","kind":"arxiv","version":1},"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":"sha256:05fa82e1ce0f2ae4f80815b2949eafe3e7a78da50944b0ba141abb7dfa781dfe","target":"record","created_at":"2026-07-03T01:17:48Z","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":"c1226eb6f3bc0cadfcf01bf565f2131dc192cdaa07bf49029244327f2d5ea06e","cross_cats_sorted":["cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-02T15:30:26Z","title_canon_sha256":"109aa3140239b2a6ac006c42f693b33b608b1bc300c13b4929425791ee9b1bbf"},"schema_version":"1.0","source":{"id":"2607.02322","kind":"arxiv","version":1}},"canonical_sha256":"f0bf106ebe6041fdfc12115abc621790f8dfd2de2a178fc87c587b783b8540e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f0bf106ebe6041fdfc12115abc621790f8dfd2de2a178fc87c587b783b8540e6","first_computed_at":"2026-07-03T01:17:48.450856Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-03T01:17:48.450856Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"XB0KLrE/G52wZ+5gVHekZ48Lote4ef3bEwbSrw/+sZRNSscyOUOXicBed19tII0lSJzgK0qDFHHSxD3NErELAw==","signature_status":"signed_v1","signed_at":"2026-07-03T01:17:48.451241Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.02322","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:05fa82e1ce0f2ae4f80815b2949eafe3e7a78da50944b0ba141abb7dfa781dfe","sha256:7d772ec179c66e085146df1061fb05536a07bb17253d2be586ab2c87fcfef1eb"],"state_sha256":"bdd15c94f3e5b41279576cae7f9bb1f9b5d6eabcc77d71e43a5368515f8e637f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OUhzuqKK4AZ+UzfINHtFPpIstAPBSf2Xzfi+3yzNwOaKkZiioSddc3lq70Ln9ZeXFR+Ftmnu7qq/fV/mE2l7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-05T02:56:19.753142Z","bundle_sha256":"8504228abd4ef96ef74059b9fb8f0f861a2880dc8396ff3e69f059161da7bcae"}}