{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MDUHGJJQZ6GNSSYSRGBLASML57","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":"0e6e07d2a1af3689c8c304154b7311b546f62e0b0c2e04f55a1d172bc00c107a","cross_cats_sorted":["cs.AI","cs.ET"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-19T12:56:00Z","title_canon_sha256":"68ba7b10ba4fba0cc88fb4a3d016493446021aa7f1295f0ad82e75d1d7604fe8"},"schema_version":"1.0","source":{"id":"2405.11537","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.11537","created_at":"2026-07-05T08:51:52Z"},{"alias_kind":"arxiv_version","alias_value":"2405.11537v3","created_at":"2026-07-05T08:51:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.11537","created_at":"2026-07-05T08:51:52Z"},{"alias_kind":"pith_short_12","alias_value":"MDUHGJJQZ6GN","created_at":"2026-07-05T08:51:52Z"},{"alias_kind":"pith_short_16","alias_value":"MDUHGJJQZ6GNSSYS","created_at":"2026-07-05T08:51:52Z"},{"alias_kind":"pith_short_8","alias_value":"MDUHGJJQ","created_at":"2026-07-05T08:51:52Z"}],"graph_snapshots":[{"event_id":"sha256:b74d8383e9001559183a0cdf2d05d0a613a2fb5fbf4f6710fe37a21c046bb02b","target":"graph","created_at":"2026-07-05T08:51:52Z","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/2405.11537/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The advent of immersive Virtual Reality applications has transformed various domains, yet their integration with advanced artificial intelligence technologies like Visual Language Models remains underexplored. This study introduces a pioneering approach utilizing VLMs within VR environments to enhance user interaction and task efficiency. Leveraging the Unity engine and a custom-developed VLM, our system facilitates real-time, intuitive user interactions through natural language processing, without relying on visual text instructions. The incorporation of speech-to-text and text-to-speech tech","authors_text":"Artem Lykov, Daria Trinitatova, Dzmitry Tsetserukou, Mikhail Konenkov","cross_cats":["cs.AI","cs.ET"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-19T12:56:00Z","title":"VR-GPT: Visual Language Model for Intelligent Virtual Reality Applications"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.11537","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":"sha256:1365c9749b09b43fbdff350118cfb42e150448785c468458132e829c3dcc41b2","target":"record","created_at":"2026-07-05T08:51:52Z","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":"0e6e07d2a1af3689c8c304154b7311b546f62e0b0c2e04f55a1d172bc00c107a","cross_cats_sorted":["cs.AI","cs.ET"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.RO","submitted_at":"2024-05-19T12:56:00Z","title_canon_sha256":"68ba7b10ba4fba0cc88fb4a3d016493446021aa7f1295f0ad82e75d1d7604fe8"},"schema_version":"1.0","source":{"id":"2405.11537","kind":"arxiv","version":3}},"canonical_sha256":"60e8732530cf8cd94b128982b0498beff5f930341e0ea3a9060ea9ab316d4b69","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"60e8732530cf8cd94b128982b0498beff5f930341e0ea3a9060ea9ab316d4b69","first_computed_at":"2026-07-05T08:51:52.393085Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:51:52.393085Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vfn4d+LdQsOGDK8g/kiXMirDBlQVtZ0YKTlUDTnpIW+5KvCNNmVPEt0/elAEIAROLvSpkl0uQwK+ADd4DRBSCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:51:52.393545Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.11537","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1365c9749b09b43fbdff350118cfb42e150448785c468458132e829c3dcc41b2","sha256:b74d8383e9001559183a0cdf2d05d0a613a2fb5fbf4f6710fe37a21c046bb02b"],"state_sha256":"324f8df3cf739eeb52fc7c7ce3f0a03eb4f81bdde60fa241d256176f04b4dbdc"}