{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:72KSMYSD74S63VPSBBTAIXMQWI","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":"52a24452d43f949ec079b33f8254cf2921a6d1bff0d15a72bf27fcfc0a97b5e4","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-11-07T16:30:12Z","title_canon_sha256":"fa893f0af03db33fbb5a33178ef6a77303c505a8370977c21403de879f237944"},"schema_version":"1.0","source":{"id":"2311.04107","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.04107","created_at":"2026-07-05T07:10:11Z"},{"alias_kind":"arxiv_version","alias_value":"2311.04107v1","created_at":"2026-07-05T07:10:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04107","created_at":"2026-07-05T07:10:11Z"},{"alias_kind":"pith_short_12","alias_value":"72KSMYSD74S6","created_at":"2026-07-05T07:10:11Z"},{"alias_kind":"pith_short_16","alias_value":"72KSMYSD74S63VPS","created_at":"2026-07-05T07:10:11Z"},{"alias_kind":"pith_short_8","alias_value":"72KSMYSD","created_at":"2026-07-05T07:10:11Z"}],"graph_snapshots":[{"event_id":"sha256:1e45fdabe9a3ec82e12800f280d1d50368c600c26fe3f97d88f6ea75c0615c34","target":"graph","created_at":"2026-07-05T07:10:11Z","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/2311.04107/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Visual object navigation using learning methods is one of the key tasks in mobile robotics. This paper introduces a new representation of a scene semantic map formed during the embodied agent interaction with the indoor environment. It is based on a neural network method that adjusts the weights of the segmentation model with backpropagation of the predicted fusion loss values during inference on a regular (backward) or delayed (forward) image sequence. We have implemented this representation into a full-fledged navigation approach called SkillTron, which can select robot skills from end-to-en","authors_text":"Aleksandr Panov, Aleksei Staroverov, Dmitry Yudin, Kirill Muravyev, Tatiana Zemskova","cross_cats":["cs.CV"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-11-07T16:30:12Z","title":"Interactive Semantic Map Representation for Skill-based Visual Object Navigation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04107","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:cfdab5a5acd7f6328280eb36b91e383b50dae7f675da331ed56639aa3b108b89","target":"record","created_at":"2026-07-05T07:10:11Z","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":"52a24452d43f949ec079b33f8254cf2921a6d1bff0d15a72bf27fcfc0a97b5e4","cross_cats_sorted":["cs.CV"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-11-07T16:30:12Z","title_canon_sha256":"fa893f0af03db33fbb5a33178ef6a77303c505a8370977c21403de879f237944"},"schema_version":"1.0","source":{"id":"2311.04107","kind":"arxiv","version":1}},"canonical_sha256":"fe95266243ff25edd5f20866045d90b21fa66955c58d84cb5e0defef075c13be","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe95266243ff25edd5f20866045d90b21fa66955c58d84cb5e0defef075c13be","first_computed_at":"2026-07-05T07:10:11.094906Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:10:11.094906Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kBaRTEMzy80DaXvGd5SDR/YS6iogG4yeG2bURyfaRjZyUk1hpBuRCx+anDWdYHburAiiVyg1tJxGO7yKB/fyCw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:10:11.095528Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.04107","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cfdab5a5acd7f6328280eb36b91e383b50dae7f675da331ed56639aa3b108b89","sha256:1e45fdabe9a3ec82e12800f280d1d50368c600c26fe3f97d88f6ea75c0615c34"],"state_sha256":"3f706cf4449be23b3c0869b275b2718c890754d38ea214a5d610599da4ac75c8"}