{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:7XDCRNBAFOL6LIXP6ECJOSTWCP","short_pith_number":"pith:7XDCRNBA","schema_version":"1.0","canonical_sha256":"fdc628b4202b97e5a2eff104974a7613fb076cd87b975a9fadffbff838db4cd2","source":{"kind":"arxiv","id":"2409.11764","version":2},"attestation_state":"computed","paper":{"title":"One Map to Find Them All: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Finn Lukas Busch, Jes\\'us Ortega-Peimbert, Olov Andersson, Quantao Yang, Timon Homberger","submitted_at":"2024-09-18T07:44:08Z","abstract_excerpt":"The capability to efficiently search for objects in complex environments is fundamental for many real-world robot applications. Recent advances in open-vocabulary vision models have resulted in semantically-informed object navigation methods that allow a robot to search for an arbitrary object without prior training. However, these zero-shot methods have so far treated the environment as unknown for each consecutive query. In this paper we introduce a new benchmark for zero-shot multi-object navigation, allowing the robot to leverage information gathered from previous searches to more efficien"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2409.11764","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2024-09-18T07:44:08Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1a32bae3e18a51d8d1c07541875f15ca1816c39696869d84d18b6d25dce196c2","abstract_canon_sha256":"d43a793a3b603b17ef7b581baa20e9ee6ff8c7b3260f2ceebd61c0aacd5abf83"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:22:49.932351Z","signature_b64":"2+qTe+pGB76za9q4INGnNI/ixCC2S7PiwqoInz6gghT2HjNin5VT5Kne87Ywgbe73bhOHNackJVqtrFsGyyGBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fdc628b4202b97e5a2eff104974a7613fb076cd87b975a9fadffbff838db4cd2","last_reissued_at":"2026-07-05T10:22:49.931563Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:22:49.931563Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"One Map to Find Them All: Real-time Open-Vocabulary Mapping for Zero-shot Multi-Object Navigation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.RO","authors_text":"Finn Lukas Busch, Jes\\'us Ortega-Peimbert, Olov Andersson, Quantao Yang, Timon Homberger","submitted_at":"2024-09-18T07:44:08Z","abstract_excerpt":"The capability to efficiently search for objects in complex environments is fundamental for many real-world robot applications. Recent advances in open-vocabulary vision models have resulted in semantically-informed object navigation methods that allow a robot to search for an arbitrary object without prior training. However, these zero-shot methods have so far treated the environment as unknown for each consecutive query. In this paper we introduce a new benchmark for zero-shot multi-object navigation, allowing the robot to leverage information gathered from previous searches to more efficien"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.11764","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/2409.11764/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2409.11764","created_at":"2026-07-05T10:22:49.931666+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.11764v2","created_at":"2026-07-05T10:22:49.931666+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.11764","created_at":"2026-07-05T10:22:49.931666+00:00"},{"alias_kind":"pith_short_12","alias_value":"7XDCRNBAFOL6","created_at":"2026-07-05T10:22:49.931666+00:00"},{"alias_kind":"pith_short_16","alias_value":"7XDCRNBAFOL6LIXP","created_at":"2026-07-05T10:22:49.931666+00:00"},{"alias_kind":"pith_short_8","alias_value":"7XDCRNBA","created_at":"2026-07-05T10:22:49.931666+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.26046","citing_title":"RoboAtlas: Contextual Active SLAM","ref_index":35,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP","json":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP.json","graph_json":"https://pith.science/api/pith-number/7XDCRNBAFOL6LIXP6ECJOSTWCP/graph.json","events_json":"https://pith.science/api/pith-number/7XDCRNBAFOL6LIXP6ECJOSTWCP/events.json","paper":"https://pith.science/paper/7XDCRNBA"},"agent_actions":{"view_html":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP","download_json":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP.json","view_paper":"https://pith.science/paper/7XDCRNBA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.11764&json=true","fetch_graph":"https://pith.science/api/pith-number/7XDCRNBAFOL6LIXP6ECJOSTWCP/graph.json","fetch_events":"https://pith.science/api/pith-number/7XDCRNBAFOL6LIXP6ECJOSTWCP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP/action/storage_attestation","attest_author":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP/action/author_attestation","sign_citation":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP/action/citation_signature","submit_replication":"https://pith.science/pith/7XDCRNBAFOL6LIXP6ECJOSTWCP/action/replication_record"}},"created_at":"2026-07-05T10:22:49.931666+00:00","updated_at":"2026-07-05T10:22:49.931666+00:00"}