{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OWHULQ2MGZQCK24QETRFXS7XBY","short_pith_number":"pith:OWHULQ2M","canonical_record":{"source":{"id":"2403.10036","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-15T05:59:10Z","cross_cats_sorted":[],"title_canon_sha256":"8efee621096ac0bbb68b72468180a8f5c6f068bd26ee4565c7b66722d3d4b3bc","abstract_canon_sha256":"b6d3dfa22035e63f22d87924eaab67b4eb1ae8087b868b63505168e894522f0d"},"schema_version":"1.0"},"canonical_sha256":"758f45c34c3660256b9024e25bcbf70e37cbfefa4df0efe463e3c130093a625c","source":{"kind":"arxiv","id":"2403.10036","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.10036","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"arxiv_version","alias_value":"2403.10036v1","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10036","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_12","alias_value":"OWHULQ2MGZQC","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_16","alias_value":"OWHULQ2MGZQCK24Q","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_8","alias_value":"OWHULQ2M","created_at":"2026-07-05T07:56:29Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OWHULQ2MGZQCK24QETRFXS7XBY","target":"record","payload":{"canonical_record":{"source":{"id":"2403.10036","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-15T05:59:10Z","cross_cats_sorted":[],"title_canon_sha256":"8efee621096ac0bbb68b72468180a8f5c6f068bd26ee4565c7b66722d3d4b3bc","abstract_canon_sha256":"b6d3dfa22035e63f22d87924eaab67b4eb1ae8087b868b63505168e894522f0d"},"schema_version":"1.0"},"canonical_sha256":"758f45c34c3660256b9024e25bcbf70e37cbfefa4df0efe463e3c130093a625c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:56:29.005848Z","signature_b64":"gwrK9Ze6mdQw0nCp/lSJsQmus/pBCs1+UY7tht12wpycnLVvCInJ3sEbBGb1XXIfxYcdjP+VWRT7pii3sbz2DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"758f45c34c3660256b9024e25bcbf70e37cbfefa4df0efe463e3c130093a625c","last_reissued_at":"2026-07-05T07:56:29.005362Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:56:29.005362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.10036","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":"2026-07-05T07:56:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wVBTG8OlVGW66gYKU1HppnDQNtJjSarCm84SNTNN3pFAvD9TyiCxmRyaEs6UPWUn8yQYWrRJOnptpdRP/G+DAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:29:46.490755Z"},"content_sha256":"7e41761e4ecc995f218001749c47e38cb9ab8ce219d9383b0d71164957d0ae48","schema_version":"1.0","event_id":"sha256:7e41761e4ecc995f218001749c47e38cb9ab8ce219d9383b0d71164957d0ae48"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OWHULQ2MGZQCK24QETRFXS7XBY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SparseFusion: Efficient Sparse Multi-Modal Fusion Framework for Long-Range 3D Perception","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Hong Chang, Hongyang Li, Naiyan Wang, Yiheng Li, Zehao Huang","submitted_at":"2024-03-15T05:59:10Z","abstract_excerpt":"Multi-modal 3D object detection has exhibited significant progress in recent years. However, most existing methods can hardly scale to long-range scenarios due to their reliance on dense 3D features, which substantially escalate computational demands and memory usage. In this paper, we introduce SparseFusion, a novel multi-modal fusion framework fully built upon sparse 3D features to facilitate efficient long-range perception. The core of our method is the Sparse View Transformer module, which selectively lifts regions of interest in 2D image space into the unified 3D space. The proposed modul"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10036","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/2403.10036/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":"2026-07-05T07:56:29Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w1neHnEouflWYzpESxZJGqOpFAqaRFl2KWR7G+R7d2iQJvuAGU0hZs7pdg2P/fLsiyBPsoB3XqxQgpwMzujvDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:29:46.491248Z"},"content_sha256":"2c9d6d91dd29f856b1b6dca042faa12cfb2fd6a253fed99491a10eb320e28683","schema_version":"1.0","event_id":"sha256:2c9d6d91dd29f856b1b6dca042faa12cfb2fd6a253fed99491a10eb320e28683"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OWHULQ2MGZQCK24QETRFXS7XBY/bundle.json","state_url":"https://pith.science/pith/OWHULQ2MGZQCK24QETRFXS7XBY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OWHULQ2MGZQCK24QETRFXS7XBY/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":"2026-08-09T15:29:46Z","links":{"resolver":"https://pith.science/pith/OWHULQ2MGZQCK24QETRFXS7XBY","bundle":"https://pith.science/pith/OWHULQ2MGZQCK24QETRFXS7XBY/bundle.json","state":"https://pith.science/pith/OWHULQ2MGZQCK24QETRFXS7XBY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OWHULQ2MGZQCK24QETRFXS7XBY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OWHULQ2MGZQCK24QETRFXS7XBY","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":"b6d3dfa22035e63f22d87924eaab67b4eb1ae8087b868b63505168e894522f0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-15T05:59:10Z","title_canon_sha256":"8efee621096ac0bbb68b72468180a8f5c6f068bd26ee4565c7b66722d3d4b3bc"},"schema_version":"1.0","source":{"id":"2403.10036","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.10036","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"arxiv_version","alias_value":"2403.10036v1","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10036","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_12","alias_value":"OWHULQ2MGZQC","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_16","alias_value":"OWHULQ2MGZQCK24Q","created_at":"2026-07-05T07:56:29Z"},{"alias_kind":"pith_short_8","alias_value":"OWHULQ2M","created_at":"2026-07-05T07:56:29Z"}],"graph_snapshots":[{"event_id":"sha256:2c9d6d91dd29f856b1b6dca042faa12cfb2fd6a253fed99491a10eb320e28683","target":"graph","created_at":"2026-07-05T07:56:29Z","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/2403.10036/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-modal 3D object detection has exhibited significant progress in recent years. However, most existing methods can hardly scale to long-range scenarios due to their reliance on dense 3D features, which substantially escalate computational demands and memory usage. In this paper, we introduce SparseFusion, a novel multi-modal fusion framework fully built upon sparse 3D features to facilitate efficient long-range perception. The core of our method is the Sparse View Transformer module, which selectively lifts regions of interest in 2D image space into the unified 3D space. The proposed modul","authors_text":"Hong Chang, Hongyang Li, Naiyan Wang, Yiheng Li, Zehao Huang","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-15T05:59:10Z","title":"SparseFusion: Efficient Sparse Multi-Modal Fusion Framework for Long-Range 3D Perception"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10036","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":"sha256:7e41761e4ecc995f218001749c47e38cb9ab8ce219d9383b0d71164957d0ae48","target":"record","created_at":"2026-07-05T07:56:29Z","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":"b6d3dfa22035e63f22d87924eaab67b4eb1ae8087b868b63505168e894522f0d","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-15T05:59:10Z","title_canon_sha256":"8efee621096ac0bbb68b72468180a8f5c6f068bd26ee4565c7b66722d3d4b3bc"},"schema_version":"1.0","source":{"id":"2403.10036","kind":"arxiv","version":1}},"canonical_sha256":"758f45c34c3660256b9024e25bcbf70e37cbfefa4df0efe463e3c130093a625c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"758f45c34c3660256b9024e25bcbf70e37cbfefa4df0efe463e3c130093a625c","first_computed_at":"2026-07-05T07:56:29.005362Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:56:29.005362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"gwrK9Ze6mdQw0nCp/lSJsQmus/pBCs1+UY7tht12wpycnLVvCInJ3sEbBGb1XXIfxYcdjP+VWRT7pii3sbz2DA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:56:29.005848Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.10036","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:7e41761e4ecc995f218001749c47e38cb9ab8ce219d9383b0d71164957d0ae48","sha256:2c9d6d91dd29f856b1b6dca042faa12cfb2fd6a253fed99491a10eb320e28683"],"state_sha256":"e2ff0e20af975a7def903672d77540a7afa0e8daa104fed040d92ac6a26fb3d7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"4ThjWQuZK11Cm1NbS03WZVy69ZbAJs407ZAvSfyVwkFTMuyhA+EAp+46+zLZfVuYkGyL99Iga+dH09nf0EXaAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:29:46.494981Z","bundle_sha256":"bfc961720ba0781c1e9ae1e7b87c2fff89176e59536c5ce2900e9898b5b25774"}}