{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:56KQOOUOGT3ZN2P4PMQCMOLDWK","short_pith_number":"pith:56KQOOUO","canonical_record":{"source":{"id":"2505.17674","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T09:41:10Z","cross_cats_sorted":[],"title_canon_sha256":"4cb9335f84fc31d9720d251913c725abe4438db286a7b648f9b8502c2b7a0a68","abstract_canon_sha256":"8b3cc22c66aa0adf4aa377fffcad5488d2c153281d9c32a0f01882045eb46808"},"schema_version":"1.0"},"canonical_sha256":"ef95073a8e34f796e9fc7b20263963b28c883e2376e9436f84f7d4a75f0b162b","source":{"kind":"arxiv","id":"2505.17674","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17674","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17674v2","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17674","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"56KQOOUOGT3Z","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_16","alias_value":"56KQOOUOGT3ZN2P4","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_8","alias_value":"56KQOOUO","created_at":"2026-05-20T00:02:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:56KQOOUOGT3ZN2P4PMQCMOLDWK","target":"record","payload":{"canonical_record":{"source":{"id":"2505.17674","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T09:41:10Z","cross_cats_sorted":[],"title_canon_sha256":"4cb9335f84fc31d9720d251913c725abe4438db286a7b648f9b8502c2b7a0a68","abstract_canon_sha256":"8b3cc22c66aa0adf4aa377fffcad5488d2c153281d9c32a0f01882045eb46808"},"schema_version":"1.0"},"canonical_sha256":"ef95073a8e34f796e9fc7b20263963b28c883e2376e9436f84f7d4a75f0b162b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-20T00:02:50.594301Z","signature_b64":"3FrGwEMZOhCwQcCjUF++nQgsGie+2ekOiXBuqAYG4iua5aWVC2VoWujA24LOpnzEoui+BSDEpPeAFGMl2fsRCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ef95073a8e34f796e9fc7b20263963b28c883e2376e9436f84f7d4a75f0b162b","last_reissued_at":"2026-05-20T00:02:50.593537Z","signature_status":"signed_v1","first_computed_at":"2026-05-20T00:02:50.593537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.17674","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":"2026-05-20T00:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D7KWuXnLlL0Pm7zozlz7VZLcBK2f1bSdHdZ2UY6+KsiH2hVlIlwt/OZsP53WxFpW5Lg0NtzDgDLWPI114fP/Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T10:04:00.462293Z"},"content_sha256":"4d37bde1aff19b768f62dcdc36bc6c96199d240fddaf442f9fb62035879c8790","schema_version":"1.0","event_id":"sha256:4d37bde1aff19b768f62dcdc36bc6c96199d240fddaf442f9fb62035879c8790"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:56KQOOUOGT3ZN2P4PMQCMOLDWK","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Xu, Guoqi Li, Peixi Wu, Shaowei Gu, Xinhao Luo, Xuerui Qiu, Yaozhi Wen, Yuqi Pan","submitted_at":"2025-05-23T09:41:10Z","abstract_excerpt":"Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing SNNs still exhibit a significant performance gap compared to Artificial Neural Networks (ANNs) due to inadequate pre-training strategies. These limitations manifest as restricted generalization ability, task specificity, and a lack of multimodal understanding, particularly in challenging tasks such as multimodal question answering and zero-shot 3D classification. To overcome these challenges, we propose a Spike-based Vision-Language (SVL) pretraining framework that empowers "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17674","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/2505.17674/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":"2026-05-20T00:02:50Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OVW6N+zG3KzNW+yKqDAvkHg6U5e7ktgiJaezvZBJXMMjVREdXJ9aVNNZxwWa6NYZEjTStHOJMCdoQ5sj7k1CAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-25T10:04:00.462830Z"},"content_sha256":"b924c2b836715539c69f629da6cb0b630243f850dcd4ce957fe4c6582887c64b","schema_version":"1.0","event_id":"sha256:b924c2b836715539c69f629da6cb0b630243f850dcd4ce957fe4c6582887c64b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/bundle.json","state_url":"https://pith.science/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/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":"2026-05-25T10:04:00Z","links":{"resolver":"https://pith.science/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK","bundle":"https://pith.science/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/bundle.json","state":"https://pith.science/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/state.json","well_known_bundle":"https://pith.science/.well-known/pith/56KQOOUOGT3ZN2P4PMQCMOLDWK/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:56KQOOUOGT3ZN2P4PMQCMOLDWK","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":"8b3cc22c66aa0adf4aa377fffcad5488d2c153281d9c32a0f01882045eb46808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T09:41:10Z","title_canon_sha256":"4cb9335f84fc31d9720d251913c725abe4438db286a7b648f9b8502c2b7a0a68"},"schema_version":"1.0","source":{"id":"2505.17674","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.17674","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"arxiv_version","alias_value":"2505.17674v2","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.17674","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_12","alias_value":"56KQOOUOGT3Z","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_16","alias_value":"56KQOOUOGT3ZN2P4","created_at":"2026-05-20T00:02:50Z"},{"alias_kind":"pith_short_8","alias_value":"56KQOOUO","created_at":"2026-05-20T00:02:50Z"}],"graph_snapshots":[{"event_id":"sha256:b924c2b836715539c69f629da6cb0b630243f850dcd4ce957fe4c6582887c64b","target":"graph","created_at":"2026-05-20T00:02:50Z","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/2505.17674/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spiking Neural Networks (SNNs) provide an energy-efficient way to extract 3D spatio-temporal features. However, existing SNNs still exhibit a significant performance gap compared to Artificial Neural Networks (ANNs) due to inadequate pre-training strategies. These limitations manifest as restricted generalization ability, task specificity, and a lack of multimodal understanding, particularly in challenging tasks such as multimodal question answering and zero-shot 3D classification. To overcome these challenges, we propose a Spike-based Vision-Language (SVL) pretraining framework that empowers ","authors_text":"Bo Xu, Guoqi Li, Peixi Wu, Shaowei Gu, Xinhao Luo, Xuerui Qiu, Yaozhi Wen, Yuqi Pan","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T09:41:10Z","title":"SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.17674","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":"sha256:4d37bde1aff19b768f62dcdc36bc6c96199d240fddaf442f9fb62035879c8790","target":"record","created_at":"2026-05-20T00:02:50Z","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":"8b3cc22c66aa0adf4aa377fffcad5488d2c153281d9c32a0f01882045eb46808","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-23T09:41:10Z","title_canon_sha256":"4cb9335f84fc31d9720d251913c725abe4438db286a7b648f9b8502c2b7a0a68"},"schema_version":"1.0","source":{"id":"2505.17674","kind":"arxiv","version":2}},"canonical_sha256":"ef95073a8e34f796e9fc7b20263963b28c883e2376e9436f84f7d4a75f0b162b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ef95073a8e34f796e9fc7b20263963b28c883e2376e9436f84f7d4a75f0b162b","first_computed_at":"2026-05-20T00:02:50.593537Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:02:50.593537Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"3FrGwEMZOhCwQcCjUF++nQgsGie+2ekOiXBuqAYG4iua5aWVC2VoWujA24LOpnzEoui+BSDEpPeAFGMl2fsRCQ==","signature_status":"signed_v1","signed_at":"2026-05-20T00:02:50.594301Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.17674","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:4d37bde1aff19b768f62dcdc36bc6c96199d240fddaf442f9fb62035879c8790","sha256:b924c2b836715539c69f629da6cb0b630243f850dcd4ce957fe4c6582887c64b"],"state_sha256":"6bd990d0af0ccd47086f66c7b8428595a90f61bb3e5e80b274f09f0d95891115"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D/8sGmcHMOc00TRBxUlHkjs0y1LmZL4YvWMcvwUF28j6UStBgrfSRg2cvplWJ8mhV8/KXO5mmTn4NKI0v1ZEDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-25T10:04:00.465951Z","bundle_sha256":"227c08fa7387df30650fb68cc6dde654692dc786d5c412c76ef5793cc51a4686"}}