{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BQRY6DFK5VQNAUB76FFGW4CEDL","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":"51284433b8c2841316932c14be27287feda0fbee6fa23fd085067aba0de20d40","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-03-12T22:33:08Z","title_canon_sha256":"03dc8293f59b6bd1faeb7f6e3af9fa94432cf90862205d1ed4408583234cd4cb"},"schema_version":"1.0","source":{"id":"2403.08109","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.08109","created_at":"2026-07-05T09:55:32Z"},{"alias_kind":"arxiv_version","alias_value":"2403.08109v3","created_at":"2026-07-05T09:55:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.08109","created_at":"2026-07-05T09:55:32Z"},{"alias_kind":"pith_short_12","alias_value":"BQRY6DFK5VQN","created_at":"2026-07-05T09:55:32Z"},{"alias_kind":"pith_short_16","alias_value":"BQRY6DFK5VQNAUB7","created_at":"2026-07-05T09:55:32Z"},{"alias_kind":"pith_short_8","alias_value":"BQRY6DFK","created_at":"2026-07-05T09:55:32Z"}],"graph_snapshots":[{"event_id":"sha256:ed00a04524cb286b14f36c471b97599080c0b6783c5a116080ccebe47cb3b65b","target":"graph","created_at":"2026-07-05T09:55:32Z","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/2403.08109/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Humans excel at efficiently navigating through crowds without collision by focusing on specific visual regions relevant to navigation. However, most robotic visual navigation methods rely on deep learning models pre-trained on vision tasks, which prioritize salient objects -- not necessarily relevant to navigation and potentially misleading. Alternative approaches train specialized navigation models from scratch, requiring significant computation. On the other hand, self-supervised learning has revolutionized computer vision and natural language processing, but its application to robotic navig","authors_text":"Amirreza Payandeh, Junzhe Wang, Mohammad Nazeri, Xuesu Xiao","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-03-12T22:33:08Z","title":"VANP: Learning Where to See for Navigation with Self-Supervised Vision-Action Pre-Training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.08109","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":"sha256:94bcd5e8a0db96c7d50cb09200b9d40a232a1f07010fa09671ea8f7b96065813","target":"record","created_at":"2026-07-05T09:55:32Z","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":"51284433b8c2841316932c14be27287feda0fbee6fa23fd085067aba0de20d40","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2024-03-12T22:33:08Z","title_canon_sha256":"03dc8293f59b6bd1faeb7f6e3af9fa94432cf90862205d1ed4408583234cd4cb"},"schema_version":"1.0","source":{"id":"2403.08109","kind":"arxiv","version":3}},"canonical_sha256":"0c238f0caaed60d0503ff14a6b70441af456ccf33b2703966fb6b0c1d59abb8d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0c238f0caaed60d0503ff14a6b70441af456ccf33b2703966fb6b0c1d59abb8d","first_computed_at":"2026-07-05T09:55:32.813999Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:55:32.813999Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ch75gZPEKBvhjBGLbadRoqbjNeYYZ0qlZ7FIVJMtE7yZcDLPPRnZUDLIzj0XvTQwtoh9hfqFu327NuGpVyyBDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:55:32.814511Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.08109","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:94bcd5e8a0db96c7d50cb09200b9d40a232a1f07010fa09671ea8f7b96065813","sha256:ed00a04524cb286b14f36c471b97599080c0b6783c5a116080ccebe47cb3b65b"],"state_sha256":"708c6b714855936f445409b1f4843cb7c24dbbbcb0472ba7a2e7ad643ddc66fb"}