{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:TGOSPOINPKX5VW5X4MXJF3NKNY","short_pith_number":"pith:TGOSPOIN","canonical_record":{"source":{"id":"2411.00151","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T18:58:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e3c920610a5b3ac0344172ec7f0c1c6a887b22d9da94adac9413e03bdf0751c3","abstract_canon_sha256":"09adfb2364263523d55cf9ca66fc74f5c9940762c4076dbb650d00872897563f"},"schema_version":"1.0"},"canonical_sha256":"999d27b90d7aafdadbb7e32e92edaa6e1aed76cc1241303f88f9f231ec2fb2c6","source":{"kind":"arxiv","id":"2411.00151","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.00151","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"arxiv_version","alias_value":"2411.00151v1","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.00151","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_12","alias_value":"TGOSPOINPKX5","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_16","alias_value":"TGOSPOINPKX5VW5X","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_8","alias_value":"TGOSPOIN","created_at":"2026-07-05T09:29:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:TGOSPOINPKX5VW5X4MXJF3NKNY","target":"record","payload":{"canonical_record":{"source":{"id":"2411.00151","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T18:58:40Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"e3c920610a5b3ac0344172ec7f0c1c6a887b22d9da94adac9413e03bdf0751c3","abstract_canon_sha256":"09adfb2364263523d55cf9ca66fc74f5c9940762c4076dbb650d00872897563f"},"schema_version":"1.0"},"canonical_sha256":"999d27b90d7aafdadbb7e32e92edaa6e1aed76cc1241303f88f9f231ec2fb2c6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:29:38.358333Z","signature_b64":"MOkiKpKJshYb9JguKUutgpcgRklumQryjG42JnF5CdtblAl+H8K33jVGY5VlwL9vEbLRaQ6v9IQ7gYshPVLdCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"999d27b90d7aafdadbb7e32e92edaa6e1aed76cc1241303f88f9f231ec2fb2c6","last_reissued_at":"2026-07-05T09:29:38.357878Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:29:38.357878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2411.00151","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:29:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"13a7t7DnWrCmnP8mLJ9A4lYry4exzyNu6rIbDTe9Tr0Pet1jJotJJs46Ydn6RT5n0w0wEHowBVykZgUxYeJPAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:25:58.289732Z"},"content_sha256":"18196325e4c9dff6c11c2a756f8b0e4b154141c6b6d56a3265abd41759ee0df7","schema_version":"1.0","event_id":"sha256:18196325e4c9dff6c11c2a756f8b0e4b154141c6b6d56a3265abd41759ee0df7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:TGOSPOINPKX5VW5X4MXJF3NKNY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"NIMBA: Towards Robust and Principled Processing of Point Clouds With SSMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Antonio Orvieto, Destiny Okpekpe, Nursena K\\\"opr\\\"uc\\\"u","submitted_at":"2024-10-31T18:58:40Z","abstract_excerpt":"Transformers have become dominant in large-scale deep learning tasks across various domains, including text, 2D and 3D vision. However, the quadratic complexity of their attention mechanism limits their efficiency as the sequence length increases, particularly in high-resolution 3D data such as point clouds. Recently, state space models (SSMs) like Mamba have emerged as promising alternatives, offering linear complexity, scalability, and high performance in long-sequence tasks. The key challenge in the application of SSMs in this domain lies in reconciling the non-sequential structure of point"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.00151","kind":"arxiv","version":1},"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/2411.00151/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":"2026-07-05T09:29:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YGcWgRcpfeQthRBDICrILW2HLbBNDmGAE7Yj7Kj9k7f/4C7lM3/ug9Kn/cRmHWmrslsune4yw68A86eflW/sDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T08:25:58.290258Z"},"content_sha256":"f16a9e96e8be14a3cbc79346b95ff18017a63c64b35f631f50d7ba5ef70c4060","schema_version":"1.0","event_id":"sha256:f16a9e96e8be14a3cbc79346b95ff18017a63c64b35f631f50d7ba5ef70c4060"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/bundle.json","state_url":"https://pith.science/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/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":"2026-08-09T08:25:58Z","links":{"resolver":"https://pith.science/pith/TGOSPOINPKX5VW5X4MXJF3NKNY","bundle":"https://pith.science/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/bundle.json","state":"https://pith.science/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/TGOSPOINPKX5VW5X4MXJF3NKNY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:TGOSPOINPKX5VW5X4MXJF3NKNY","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":"09adfb2364263523d55cf9ca66fc74f5c9940762c4076dbb650d00872897563f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T18:58:40Z","title_canon_sha256":"e3c920610a5b3ac0344172ec7f0c1c6a887b22d9da94adac9413e03bdf0751c3"},"schema_version":"1.0","source":{"id":"2411.00151","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.00151","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"arxiv_version","alias_value":"2411.00151v1","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.00151","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_12","alias_value":"TGOSPOINPKX5","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_16","alias_value":"TGOSPOINPKX5VW5X","created_at":"2026-07-05T09:29:38Z"},{"alias_kind":"pith_short_8","alias_value":"TGOSPOIN","created_at":"2026-07-05T09:29:38Z"}],"graph_snapshots":[{"event_id":"sha256:f16a9e96e8be14a3cbc79346b95ff18017a63c64b35f631f50d7ba5ef70c4060","target":"graph","created_at":"2026-07-05T09:29:38Z","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/2411.00151/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Transformers have become dominant in large-scale deep learning tasks across various domains, including text, 2D and 3D vision. However, the quadratic complexity of their attention mechanism limits their efficiency as the sequence length increases, particularly in high-resolution 3D data such as point clouds. Recently, state space models (SSMs) like Mamba have emerged as promising alternatives, offering linear complexity, scalability, and high performance in long-sequence tasks. The key challenge in the application of SSMs in this domain lies in reconciling the non-sequential structure of point","authors_text":"Antonio Orvieto, Destiny Okpekpe, Nursena K\\\"opr\\\"uc\\\"u","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T18:58:40Z","title":"NIMBA: Towards Robust and Principled Processing of Point Clouds With SSMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.00151","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":"sha256:18196325e4c9dff6c11c2a756f8b0e4b154141c6b6d56a3265abd41759ee0df7","target":"record","created_at":"2026-07-05T09:29:38Z","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":"09adfb2364263523d55cf9ca66fc74f5c9940762c4076dbb650d00872897563f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-10-31T18:58:40Z","title_canon_sha256":"e3c920610a5b3ac0344172ec7f0c1c6a887b22d9da94adac9413e03bdf0751c3"},"schema_version":"1.0","source":{"id":"2411.00151","kind":"arxiv","version":1}},"canonical_sha256":"999d27b90d7aafdadbb7e32e92edaa6e1aed76cc1241303f88f9f231ec2fb2c6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"999d27b90d7aafdadbb7e32e92edaa6e1aed76cc1241303f88f9f231ec2fb2c6","first_computed_at":"2026-07-05T09:29:38.357878Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:29:38.357878Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MOkiKpKJshYb9JguKUutgpcgRklumQryjG42JnF5CdtblAl+H8K33jVGY5VlwL9vEbLRaQ6v9IQ7gYshPVLdCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:29:38.358333Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.00151","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:18196325e4c9dff6c11c2a756f8b0e4b154141c6b6d56a3265abd41759ee0df7","sha256:f16a9e96e8be14a3cbc79346b95ff18017a63c64b35f631f50d7ba5ef70c4060"],"state_sha256":"257538400c5b2d834fd046319f1a0dbac43e774c9b28efd18c0e47840f3430a0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SlxeptJXst4cDCnunACh2ZWJUMHGGHebJIBH8DCk6Cg2CMx+eB0Byvjnm5TO8szRieewtcFvBfRrDEDVUtl5AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T08:25:58.296582Z","bundle_sha256":"8fe25718ba2926f1c64e92af3e415a8b14550a626a309db97b600d61ee385b1f"}}