{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:KMIMFGD7CTBFH4ZTM6QGRK66WP","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":"60867df006e536f90dde81a5e7abc37d7a3a724ec1fe3bf912dc1bc7720ab3ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-04T01:21:12Z","title_canon_sha256":"b04b9eb7b91648ff9f0a110eefd6dcad18f9929c6f05a732f2acde7636df8b51"},"schema_version":"1.0","source":{"id":"2607.16267","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.16267","created_at":"2026-07-21T00:20:09Z"},{"alias_kind":"arxiv_version","alias_value":"2607.16267v1","created_at":"2026-07-21T00:20:09Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.16267","created_at":"2026-07-21T00:20:09Z"},{"alias_kind":"pith_short_12","alias_value":"KMIMFGD7CTBF","created_at":"2026-07-21T00:20:09Z"},{"alias_kind":"pith_short_16","alias_value":"KMIMFGD7CTBFH4ZT","created_at":"2026-07-21T00:20:09Z"},{"alias_kind":"pith_short_8","alias_value":"KMIMFGD7","created_at":"2026-07-21T00:20:09Z"}],"graph_snapshots":[{"event_id":"sha256:bc2833acf02c91beba743c9a534482b9235e9762fffc9eeb34327703dc18a71e","target":"graph","created_at":"2026-07-21T00:20:09Z","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/2607.16267/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Continual learning in visual navigation remains challenging due to catastrophic forgetting and the difficulties associated with adapting to diverse and evolving environments. To address these issues, we propose Hyperbolic Dynamic Cluster Memory (HyperDCM), a structure-aware memory mechanism that enhances diffusion policy-based navigation through scene graph modeling and principled memory replay. HyperDCM extracts semantic scene triples from RGB observations using large vision-language models, encodes them into scene graph embeddings via a Relational Graph Convolutional Network (R-GCN), and pro","authors_text":"Jian Yang, Jinpeng Mi, Ke Li, Muyu Wang, Qi Wu, Shaowen Chen, Xian Wei, Xiong You, Xuan Tang, Zhengfei Lu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-04T01:21:12Z","title":"HyperDCM: Dynamic Cluster Memory Replay in Hyperbolic Space for Continual Robotic Navigation Across Scenes"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.16267","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":"sha256:4cb6402337673526db670820c615cae35996f4be1eab78d4005d4090c7c47ecf","target":"record","created_at":"2026-07-21T00:20:09Z","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":"60867df006e536f90dde81a5e7abc37d7a3a724ec1fe3bf912dc1bc7720ab3ba","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.RO","submitted_at":"2026-07-04T01:21:12Z","title_canon_sha256":"b04b9eb7b91648ff9f0a110eefd6dcad18f9929c6f05a732f2acde7636df8b51"},"schema_version":"1.0","source":{"id":"2607.16267","kind":"arxiv","version":1}},"canonical_sha256":"5310c2987f14c253f33367a068abdeb3e1e80786250c159e0f2a1e30cc9c532c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5310c2987f14c253f33367a068abdeb3e1e80786250c159e0f2a1e30cc9c532c","first_computed_at":"2026-07-21T00:20:09.341218Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T00:20:09.341218Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Ldk4M9mOp1U89h+7d2DDu217EiXIWHF/XxdtsTgh0Ib45G/Z5k37xq8MvN8wg+x++fgTdDk5kKijXP1cxPgdAA==","signature_status":"signed_v1","signed_at":"2026-07-21T00:20:09.342135Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.16267","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4cb6402337673526db670820c615cae35996f4be1eab78d4005d4090c7c47ecf","sha256:bc2833acf02c91beba743c9a534482b9235e9762fffc9eeb34327703dc18a71e"],"state_sha256":"f7285e30b624a279295a513f405445ad327d7bb57b7d2988397ce8ca854b37a9"}