{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:DY3QCFZL3ZLSWLQOQZFNW4RDUI","short_pith_number":"pith:DY3QCFZL","canonical_record":{"source":{"id":"2508.09227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T06:54:26Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"1d6466801413fd2b3d308cf8b3a08838c77e49948521bc66f8b8e941388acdff","abstract_canon_sha256":"65e092d9233b46ffb50a7a6fab5fe55127be4500a406e1ef65a2fd61635eb9f5"},"schema_version":"1.0"},"canonical_sha256":"1e3701172bde572b2e0e864adb7223a20fbd03b2a82da61f7a86c5b7b49b3955","source":{"kind":"arxiv","id":"2508.09227","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09227","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09227v1","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09227","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_12","alias_value":"DY3QCFZL3ZLS","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_16","alias_value":"DY3QCFZL3ZLSWLQO","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_8","alias_value":"DY3QCFZL","created_at":"2026-07-05T11:53:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:DY3QCFZL3ZLSWLQOQZFNW4RDUI","target":"record","payload":{"canonical_record":{"source":{"id":"2508.09227","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T06:54:26Z","cross_cats_sorted":["cs.AI","cs.CE"],"title_canon_sha256":"1d6466801413fd2b3d308cf8b3a08838c77e49948521bc66f8b8e941388acdff","abstract_canon_sha256":"65e092d9233b46ffb50a7a6fab5fe55127be4500a406e1ef65a2fd61635eb9f5"},"schema_version":"1.0"},"canonical_sha256":"1e3701172bde572b2e0e864adb7223a20fbd03b2a82da61f7a86c5b7b49b3955","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:53:10.582602Z","signature_b64":"UQyOckxwdC2kkGrnM1JJOiItXDsntzmBjWItDj7xZea04CUNnL6BHh3DU22KHk7m4G5ZfouSU7lu+n5yvtQLAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1e3701172bde572b2e0e864adb7223a20fbd03b2a82da61f7a86c5b7b49b3955","last_reissued_at":"2026-07-05T11:53:10.582118Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:53:10.582118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.09227","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":"2026-07-05T11:53:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0nJ3EteScG1ChB8Bu19vcG69N6b3+8AMameBvXjHJ8mVd3MkU6UMuZTnYIFOPKpMfoDnhzzK0cOYOZOvCwbLAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T19:09:27.254026Z"},"content_sha256":"35d7f7c48ab415987d3e89a7961964766666e1798ef0c34512ad6633d53e6dd2","schema_version":"1.0","event_id":"sha256:35d7f7c48ab415987d3e89a7961964766666e1798ef0c34512ad6633d53e6dd2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:DY3QCFZL3ZLSWLQOQZFNW4RDUI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"GSMT: Graph Fusion and Spatiotemporal TaskCorrection for Multi-Bus Trajectory Prediction","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CE"],"primary_cat":"cs.LG","authors_text":"Fan Ding, Fang Yu Leong, Hwa Hui Tew, Jia Jun Gan, Junn Yong Loo, Kar Keong Chin, Litong Liu, Susilawati, Xuewen Luo","submitted_at":"2025-08-12T06:54:26Z","abstract_excerpt":"Accurate trajectory prediction for buses is crucial in intelligent transportation systems, particularly within urban environments. In developing regions where access to multimodal data is limited, relying solely on onboard GPS data remains indispensable despite inherent challenges. To address this problem, we propose GSMT, a hybrid model that integrates a Graph Attention Network (GAT) with a sequence-to-sequence Recurrent Neural Network (RNN), and incorporates a task corrector capable of extracting complex behavioral patterns from large-scale trajectory data. The task corrector clusters histor"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09227","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/2508.09227/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":"2026-07-05T11:53:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MSlw23mvO5+OUl9ExgJjjwW4zgA/FUVem448sSLEMWQBXx1c5uREYmV6Ur1STWwj+KIaTHjzPhSn3XVusfvrDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-18T19:09:27.254425Z"},"content_sha256":"d2b56767d33cd6b3b5ae21bda39ac4ebe5d311a6c3e71f0ba3f16e0a89083fae","schema_version":"1.0","event_id":"sha256:d2b56767d33cd6b3b5ae21bda39ac4ebe5d311a6c3e71f0ba3f16e0a89083fae"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/bundle.json","state_url":"https://pith.science/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/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":"2026-07-18T19:09:27Z","links":{"resolver":"https://pith.science/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI","bundle":"https://pith.science/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/bundle.json","state":"https://pith.science/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DY3QCFZL3ZLSWLQOQZFNW4RDUI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:DY3QCFZL3ZLSWLQOQZFNW4RDUI","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":"65e092d9233b46ffb50a7a6fab5fe55127be4500a406e1ef65a2fd61635eb9f5","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T06:54:26Z","title_canon_sha256":"1d6466801413fd2b3d308cf8b3a08838c77e49948521bc66f8b8e941388acdff"},"schema_version":"1.0","source":{"id":"2508.09227","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.09227","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"arxiv_version","alias_value":"2508.09227v1","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.09227","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_12","alias_value":"DY3QCFZL3ZLS","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_16","alias_value":"DY3QCFZL3ZLSWLQO","created_at":"2026-07-05T11:53:10Z"},{"alias_kind":"pith_short_8","alias_value":"DY3QCFZL","created_at":"2026-07-05T11:53:10Z"}],"graph_snapshots":[{"event_id":"sha256:d2b56767d33cd6b3b5ae21bda39ac4ebe5d311a6c3e71f0ba3f16e0a89083fae","target":"graph","created_at":"2026-07-05T11:53:10Z","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/2508.09227/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Accurate trajectory prediction for buses is crucial in intelligent transportation systems, particularly within urban environments. In developing regions where access to multimodal data is limited, relying solely on onboard GPS data remains indispensable despite inherent challenges. To address this problem, we propose GSMT, a hybrid model that integrates a Graph Attention Network (GAT) with a sequence-to-sequence Recurrent Neural Network (RNN), and incorporates a task corrector capable of extracting complex behavioral patterns from large-scale trajectory data. The task corrector clusters histor","authors_text":"Fan Ding, Fang Yu Leong, Hwa Hui Tew, Jia Jun Gan, Junn Yong Loo, Kar Keong Chin, Litong Liu, Susilawati, Xuewen Luo","cross_cats":["cs.AI","cs.CE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T06:54:26Z","title":"GSMT: Graph Fusion and Spatiotemporal TaskCorrection for Multi-Bus Trajectory Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.09227","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":"sha256:35d7f7c48ab415987d3e89a7961964766666e1798ef0c34512ad6633d53e6dd2","target":"record","created_at":"2026-07-05T11:53:10Z","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":"65e092d9233b46ffb50a7a6fab5fe55127be4500a406e1ef65a2fd61635eb9f5","cross_cats_sorted":["cs.AI","cs.CE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2025-08-12T06:54:26Z","title_canon_sha256":"1d6466801413fd2b3d308cf8b3a08838c77e49948521bc66f8b8e941388acdff"},"schema_version":"1.0","source":{"id":"2508.09227","kind":"arxiv","version":1}},"canonical_sha256":"1e3701172bde572b2e0e864adb7223a20fbd03b2a82da61f7a86c5b7b49b3955","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1e3701172bde572b2e0e864adb7223a20fbd03b2a82da61f7a86c5b7b49b3955","first_computed_at":"2026-07-05T11:53:10.582118Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:53:10.582118Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UQyOckxwdC2kkGrnM1JJOiItXDsntzmBjWItDj7xZea04CUNnL6BHh3DU22KHk7m4G5ZfouSU7lu+n5yvtQLAA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:53:10.582602Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.09227","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:35d7f7c48ab415987d3e89a7961964766666e1798ef0c34512ad6633d53e6dd2","sha256:d2b56767d33cd6b3b5ae21bda39ac4ebe5d311a6c3e71f0ba3f16e0a89083fae"],"state_sha256":"8d0d2a196d899ac84fc868613cc5d4769c5899747c010433e4984e3c7006703c"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OdL0gBBT0Zda2dKV4eJMSgt0ORg6Ux6pB2LrjOZGyxrnMjADpmcuEvyu+fkZgkxg8BScAbSptPQakHSGN9v+Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-18T19:09:27.256640Z","bundle_sha256":"048fb2d907d93223806ac53d7114b91983395784ec5f354e5e2b9766c14a7d7e"}}