{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:J4SA37B2KJIYAA5WR6EIDLCCBB","short_pith_number":"pith:J4SA37B2","canonical_record":{"source":{"id":"2504.09540","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-13T12:10:49Z","cross_cats_sorted":[],"title_canon_sha256":"3465fefe261db0c4eaa932e12add61078f821f0b7ce124d0d09384c36e8b3e25","abstract_canon_sha256":"9cbfb26d57c5834b85f17052cd9f416cae3e0b054a0e6757f8954f1a3ab56aa6"},"schema_version":"1.0"},"canonical_sha256":"4f240dfc3a52518003b68f8881ac42086b5d12062b1d9b9ec79258b12fcc2f26","source":{"kind":"arxiv","id":"2504.09540","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.09540","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"arxiv_version","alias_value":"2504.09540v2","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.09540","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_12","alias_value":"J4SA37B2KJIY","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_16","alias_value":"J4SA37B2KJIYAA5W","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_8","alias_value":"J4SA37B2","created_at":"2026-07-05T11:43:11Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:J4SA37B2KJIYAA5WR6EIDLCCBB","target":"record","payload":{"canonical_record":{"source":{"id":"2504.09540","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-13T12:10:49Z","cross_cats_sorted":[],"title_canon_sha256":"3465fefe261db0c4eaa932e12add61078f821f0b7ce124d0d09384c36e8b3e25","abstract_canon_sha256":"9cbfb26d57c5834b85f17052cd9f416cae3e0b054a0e6757f8954f1a3ab56aa6"},"schema_version":"1.0"},"canonical_sha256":"4f240dfc3a52518003b68f8881ac42086b5d12062b1d9b9ec79258b12fcc2f26","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:43:11.009653Z","signature_b64":"8LFjIZ1+PWs1nVJbJ3/wkZ0549Ru9DS4mmfDNbmDeWc1TqiSRnCMWS/jtT1xoQqTZROEy0vNJbhXXbgsChpuAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4f240dfc3a52518003b68f8881ac42086b5d12062b1d9b9ec79258b12fcc2f26","last_reissued_at":"2026-07-05T11:43:11.009139Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:43:11.009139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2504.09540","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:43:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TeosyC9RSmlSk44/k4wJYAmTLD8iSRh8rCfJcn0FKepOxXZ18B/jcreBlFRZhyM9gVjcafZZr0XtJTxwsZp/Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:39:28.478653Z"},"content_sha256":"7f57d312e844af7131b6cf9ab6c05944bee5557caf38bc7a1557d8aca1efabcd","schema_version":"1.0","event_id":"sha256:7f57d312e844af7131b6cf9ab6c05944bee5557caf38bc7a1557d8aca1efabcd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:J4SA37B2KJIYAA5WR6EIDLCCBB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EmbodiedOcc++: Boosting Embodied 3D Occupancy Prediction with Plane Regularization and Uncertainty Sampler","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Chengyu Bai, Hao Wang, Jianing Li, Ming Lu, Shanghang Zhang, Wenzhao Zheng, Xiaoan Zhang, Xiaobao Wei, Ying Li","submitted_at":"2025-04-13T12:10:49Z","abstract_excerpt":"Online 3D occupancy prediction provides a comprehensive spatial understanding of embodied environments. While the innovative EmbodiedOcc framework utilizes 3D semantic Gaussians for progressive indoor occupancy prediction, it overlooks the geometric characteristics of indoor environments, which are primarily characterized by planar structures. This paper introduces EmbodiedOcc++, enhancing the original framework with two key innovations: a Geometry-guided Refinement Module (GRM) that constrains Gaussian updates through plane regularization, along with a Semantic-aware Uncertainty Sampler (SUS)"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.09540","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/2504.09540/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:43:11Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vz2cuvxJ8n1MgDdPXPYeJ7beFTMhPqThq/AZfgimkkeEJQLbZl8Y7qncwn7j70ypdw2/X2FvYb2B2JmqFlAsCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T18:39:28.479675Z"},"content_sha256":"ad91d7ebe3fa3294e9341696ae12acaa3154ec3be700a39986ecbc9127996991","schema_version":"1.0","event_id":"sha256:ad91d7ebe3fa3294e9341696ae12acaa3154ec3be700a39986ecbc9127996991"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/bundle.json","state_url":"https://pith.science/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-08T18:39:28Z","links":{"resolver":"https://pith.science/pith/J4SA37B2KJIYAA5WR6EIDLCCBB","bundle":"https://pith.science/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/bundle.json","state":"https://pith.science/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/J4SA37B2KJIYAA5WR6EIDLCCBB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:J4SA37B2KJIYAA5WR6EIDLCCBB","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":"9cbfb26d57c5834b85f17052cd9f416cae3e0b054a0e6757f8954f1a3ab56aa6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-13T12:10:49Z","title_canon_sha256":"3465fefe261db0c4eaa932e12add61078f821f0b7ce124d0d09384c36e8b3e25"},"schema_version":"1.0","source":{"id":"2504.09540","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.09540","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"arxiv_version","alias_value":"2504.09540v2","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.09540","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_12","alias_value":"J4SA37B2KJIY","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_16","alias_value":"J4SA37B2KJIYAA5W","created_at":"2026-07-05T11:43:11Z"},{"alias_kind":"pith_short_8","alias_value":"J4SA37B2","created_at":"2026-07-05T11:43:11Z"}],"graph_snapshots":[{"event_id":"sha256:ad91d7ebe3fa3294e9341696ae12acaa3154ec3be700a39986ecbc9127996991","target":"graph","created_at":"2026-07-05T11:43:11Z","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/2504.09540/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Online 3D occupancy prediction provides a comprehensive spatial understanding of embodied environments. While the innovative EmbodiedOcc framework utilizes 3D semantic Gaussians for progressive indoor occupancy prediction, it overlooks the geometric characteristics of indoor environments, which are primarily characterized by planar structures. This paper introduces EmbodiedOcc++, enhancing the original framework with two key innovations: a Geometry-guided Refinement Module (GRM) that constrains Gaussian updates through plane regularization, along with a Semantic-aware Uncertainty Sampler (SUS)","authors_text":"Chengyu Bai, Hao Wang, Jianing Li, Ming Lu, Shanghang Zhang, Wenzhao Zheng, Xiaoan Zhang, Xiaobao Wei, Ying Li","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-13T12:10:49Z","title":"EmbodiedOcc++: Boosting Embodied 3D Occupancy Prediction with Plane Regularization and Uncertainty Sampler"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.09540","kind":"arxiv","version":2},"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":"sha256:7f57d312e844af7131b6cf9ab6c05944bee5557caf38bc7a1557d8aca1efabcd","target":"record","created_at":"2026-07-05T11:43:11Z","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":"9cbfb26d57c5834b85f17052cd9f416cae3e0b054a0e6757f8954f1a3ab56aa6","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-13T12:10:49Z","title_canon_sha256":"3465fefe261db0c4eaa932e12add61078f821f0b7ce124d0d09384c36e8b3e25"},"schema_version":"1.0","source":{"id":"2504.09540","kind":"arxiv","version":2}},"canonical_sha256":"4f240dfc3a52518003b68f8881ac42086b5d12062b1d9b9ec79258b12fcc2f26","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4f240dfc3a52518003b68f8881ac42086b5d12062b1d9b9ec79258b12fcc2f26","first_computed_at":"2026-07-05T11:43:11.009139Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:43:11.009139Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8LFjIZ1+PWs1nVJbJ3/wkZ0549Ru9DS4mmfDNbmDeWc1TqiSRnCMWS/jtT1xoQqTZROEy0vNJbhXXbgsChpuAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:43:11.009653Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.09540","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7f57d312e844af7131b6cf9ab6c05944bee5557caf38bc7a1557d8aca1efabcd","sha256:ad91d7ebe3fa3294e9341696ae12acaa3154ec3be700a39986ecbc9127996991"],"state_sha256":"5b006941111b87dd047a6822ba5969ed523e79622fe0c59584960c1b67ae0b87"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SZ8Hl8TV6qMEoREjZWq2KS5BxgxoTiV752JwL2+r6KadrHtBawOscoZH5/PVpfiv5p1BscUNNWBpESqIqj6aDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T18:39:28.485363Z","bundle_sha256":"aea41d1c3768d3f5eb71f718a59ec25090cdad9cdb89c7254e9500a3b82f1a25"}}