{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:7R7DBJKLVKFR46FASQJBDBK3GH","short_pith_number":"pith:7R7DBJKL","canonical_record":{"source":{"id":"2607.18353","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-20T09:17:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1c2c42abffac5e00366367f2312dd90a1002561c1216ce21b3b6bd56424e1a9c","abstract_canon_sha256":"b278bfca01308a6ab4e4e8eaa568bf4082a5b6977c9e73e8198faac841d88a46"},"schema_version":"1.0"},"canonical_sha256":"fc7e30a54baa8b1e78a0941211855b31f2998351d9c771cb3e435247dca17ea5","source":{"kind":"arxiv","id":"2607.18353","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18353","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18353v1","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18353","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_12","alias_value":"7R7DBJKLVKFR","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_16","alias_value":"7R7DBJKLVKFR46FA","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_8","alias_value":"7R7DBJKL","created_at":"2026-07-22T00:22:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:7R7DBJKLVKFR46FASQJBDBK3GH","target":"record","payload":{"canonical_record":{"source":{"id":"2607.18353","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-20T09:17:58Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1c2c42abffac5e00366367f2312dd90a1002561c1216ce21b3b6bd56424e1a9c","abstract_canon_sha256":"b278bfca01308a6ab4e4e8eaa568bf4082a5b6977c9e73e8198faac841d88a46"},"schema_version":"1.0"},"canonical_sha256":"fc7e30a54baa8b1e78a0941211855b31f2998351d9c771cb3e435247dca17ea5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-22T00:22:43.104994Z","signature_b64":"pIm1erXBHLOSUuzReae+bJ61ZpVILeSbAYD2ESj3H08PAUcXlMJh+L680pRkITfdSkDapDcdc8QxelZ/PcJjDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc7e30a54baa8b1e78a0941211855b31f2998351d9c771cb3e435247dca17ea5","last_reissued_at":"2026-07-22T00:22:43.104162Z","signature_status":"signed_v1","first_computed_at":"2026-07-22T00:22:43.104162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2607.18353","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":"2026-07-22T00:22:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uwb+yDrKiLedEmOkSQ5Ag53jUh+lWi2W3joLqR0g4SfLiKWhJDSGkjjwDftKtolorFXm2VOKUMGTH3Wt+Y8hCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T21:34:18.698250Z"},"content_sha256":"1ab2b676408a3b8804edd830af7e613624e93bccf88354852134cbdb75e5323f","schema_version":"1.0","event_id":"sha256:1ab2b676408a3b8804edd830af7e613624e93bccf88354852134cbdb75e5323f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:7R7DBJKLVKFR46FASQJBDBK3GH","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MambaLSTM: A Spatio-Temporal Framework for Enhanced Traffic Accident Risk Prediction","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Muting Li, Thar Baker, Yachao Yuan, Zhen Yu, Zixiang Peng","submitted_at":"2026-07-20T09:17:58Z","abstract_excerpt":"In traffic accident risk prediction, most studies overlook the extra noise that could be incorporated when fusing temporal features into spatial features, and some models struggle to capture global correlations among spatial regions. To address these challenges, we propose a novel traffic accident risk prediction framework named MambaLSTM. First, we develop a squeeze-and-excitation temporal feature fusion module to integrate temporal information without compromising spatio-temporal integrity. Second, we introduce a new patch embedding module for effectively capturing semantic relationships amo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18353","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/2607.18353/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":"2026-07-22T00:22:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qMNcXIEACTowiBX6FHVY6fvsA0vDbRcNP+kjwoTn3IBDQBXzb3xb4dQyuKW2D31xA/JNnQoIOtLC66zKNXAkAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-02T21:34:18.698798Z"},"content_sha256":"374d09e3e8cc2bc0605c45a894729448f28bb5fbef5330bd3f96c621265ec14f","schema_version":"1.0","event_id":"sha256:374d09e3e8cc2bc0605c45a894729448f28bb5fbef5330bd3f96c621265ec14f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7R7DBJKLVKFR46FASQJBDBK3GH/bundle.json","state_url":"https://pith.science/pith/7R7DBJKLVKFR46FASQJBDBK3GH/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7R7DBJKLVKFR46FASQJBDBK3GH/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":"2026-08-02T21:34:18Z","links":{"resolver":"https://pith.science/pith/7R7DBJKLVKFR46FASQJBDBK3GH","bundle":"https://pith.science/pith/7R7DBJKLVKFR46FASQJBDBK3GH/bundle.json","state":"https://pith.science/pith/7R7DBJKLVKFR46FASQJBDBK3GH/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7R7DBJKLVKFR46FASQJBDBK3GH/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:7R7DBJKLVKFR46FASQJBDBK3GH","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":"b278bfca01308a6ab4e4e8eaa568bf4082a5b6977c9e73e8198faac841d88a46","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-20T09:17:58Z","title_canon_sha256":"1c2c42abffac5e00366367f2312dd90a1002561c1216ce21b3b6bd56424e1a9c"},"schema_version":"1.0","source":{"id":"2607.18353","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.18353","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"arxiv_version","alias_value":"2607.18353v1","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.18353","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_12","alias_value":"7R7DBJKLVKFR","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_16","alias_value":"7R7DBJKLVKFR46FA","created_at":"2026-07-22T00:22:43Z"},{"alias_kind":"pith_short_8","alias_value":"7R7DBJKL","created_at":"2026-07-22T00:22:43Z"}],"graph_snapshots":[{"event_id":"sha256:374d09e3e8cc2bc0605c45a894729448f28bb5fbef5330bd3f96c621265ec14f","target":"graph","created_at":"2026-07-22T00:22:43Z","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/2607.18353/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In traffic accident risk prediction, most studies overlook the extra noise that could be incorporated when fusing temporal features into spatial features, and some models struggle to capture global correlations among spatial regions. To address these challenges, we propose a novel traffic accident risk prediction framework named MambaLSTM. First, we develop a squeeze-and-excitation temporal feature fusion module to integrate temporal information without compromising spatio-temporal integrity. Second, we introduce a new patch embedding module for effectively capturing semantic relationships amo","authors_text":"Muting Li, Thar Baker, Yachao Yuan, Zhen Yu, Zixiang Peng","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-20T09:17:58Z","title":"MambaLSTM: A Spatio-Temporal Framework for Enhanced Traffic Accident Risk Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.18353","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":"sha256:1ab2b676408a3b8804edd830af7e613624e93bccf88354852134cbdb75e5323f","target":"record","created_at":"2026-07-22T00:22:43Z","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":"b278bfca01308a6ab4e4e8eaa568bf4082a5b6977c9e73e8198faac841d88a46","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-20T09:17:58Z","title_canon_sha256":"1c2c42abffac5e00366367f2312dd90a1002561c1216ce21b3b6bd56424e1a9c"},"schema_version":"1.0","source":{"id":"2607.18353","kind":"arxiv","version":1}},"canonical_sha256":"fc7e30a54baa8b1e78a0941211855b31f2998351d9c771cb3e435247dca17ea5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fc7e30a54baa8b1e78a0941211855b31f2998351d9c771cb3e435247dca17ea5","first_computed_at":"2026-07-22T00:22:43.104162Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-22T00:22:43.104162Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"pIm1erXBHLOSUuzReae+bJ61ZpVILeSbAYD2ESj3H08PAUcXlMJh+L680pRkITfdSkDapDcdc8QxelZ/PcJjDg==","signature_status":"signed_v1","signed_at":"2026-07-22T00:22:43.104994Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.18353","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ab2b676408a3b8804edd830af7e613624e93bccf88354852134cbdb75e5323f","sha256:374d09e3e8cc2bc0605c45a894729448f28bb5fbef5330bd3f96c621265ec14f"],"state_sha256":"70a4acca42c9680ea7965f3c80a175e52b55898965f46081a6722a5903d133b9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gprc3wj+prVzWvzPd3SxbsI0ZwvmHpBWlqaxNFTkb7GFVWg/O5jXTnOlmNTt4w4QfkXpg7s7i1ip7WgVgn7pCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-02T21:34:18.702803Z","bundle_sha256":"720c083010b698f9813db0d344228490ee7ec7928125cb706fc6cd85165e24b2"}}