{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JRY6C563REL36RZ2KUSPL4ZF7L","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":"04c4de0bd0b3a10d3b46499cf43ada06a3bccba8068be520930c4a9095f57c2f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T13:04:17Z","title_canon_sha256":"a4629e6df1b2f81dd618dd38369c231ff8b29e3decfb69b83a6743b0b0ea41fb"},"schema_version":"1.0","source":{"id":"2605.29879","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.29879","created_at":"2026-05-29T02:05:57Z"},{"alias_kind":"arxiv_version","alias_value":"2605.29879v1","created_at":"2026-05-29T02:05:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.29879","created_at":"2026-05-29T02:05:57Z"},{"alias_kind":"pith_short_12","alias_value":"JRY6C563REL3","created_at":"2026-05-29T02:05:57Z"},{"alias_kind":"pith_short_16","alias_value":"JRY6C563REL36RZ2","created_at":"2026-05-29T02:05:57Z"},{"alias_kind":"pith_short_8","alias_value":"JRY6C563","created_at":"2026-05-29T02:05:57Z"}],"graph_snapshots":[{"event_id":"sha256:9b71cbf0a9f1743a0496faf541c432adea134ec826738311d23c2c4dcc962a27","target":"graph","created_at":"2026-05-29T02:05:57Z","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/2605.29879/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Integrating open-vocabulary semantic information into dynamic 3D scene representations is essential for long-term embodied scene understanding. However, existing methods often suffer from fragile instance association due to incomplete cross-view cues, while their limited ability to handle object-level topological changes restricts long-term robotic task execution. Moreover, current 3D scene understanding methods either rely on simple feature matching without explicit spatial reasoning or assume offline ground-truth 3D geometry. To address these challenges, we present DGSG-Mind, a hybrid instan","authors_text":"Jinyan Liu, Luzhou Ge, Xiangyu Zhu, Xuesong Li","cross_cats":["cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T13:04:17Z","title":"DGSG-Mind: Dynamic 3D Gaussian Scene Graphs for Long-Term Scene Understanding and Grounding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.29879","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":"sha256:4e0265348e67f985abfbeb55e2f37ba9d0462b2b9faa2b9d1c384439b0b50e60","target":"record","created_at":"2026-05-29T02:05:57Z","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":"04c4de0bd0b3a10d3b46499cf43ada06a3bccba8068be520930c4a9095f57c2f","cross_cats_sorted":["cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2026-05-28T13:04:17Z","title_canon_sha256":"a4629e6df1b2f81dd618dd38369c231ff8b29e3decfb69b83a6743b0b0ea41fb"},"schema_version":"1.0","source":{"id":"2605.29879","kind":"arxiv","version":1}},"canonical_sha256":"4c71e177db8917bf473a5524f5f325fada085ccc28ae176ae42ed1b00d7fe884","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4c71e177db8917bf473a5524f5f325fada085ccc28ae176ae42ed1b00d7fe884","first_computed_at":"2026-05-29T02:05:57.434932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:05:57.434932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"QFfbHP+QzYzz3QM73D5o24Uuq0FB7egvasN+onoes8pCfNkb7fw37pW0SdpS9umUPu7Q3I2fJvolo/dNoFRDDA==","signature_status":"signed_v1","signed_at":"2026-05-29T02:05:57.435702Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.29879","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4e0265348e67f985abfbeb55e2f37ba9d0462b2b9faa2b9d1c384439b0b50e60","sha256:9b71cbf0a9f1743a0496faf541c432adea134ec826738311d23c2c4dcc962a27"],"state_sha256":"49cbf9dffa06373dbb2e37d87158cfabc76ae866361817b0f0ab198e4013b35e"}