{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:C4HU3WSUK6DD2AV7WSM5QROYD5","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":"385d3fbc21c7a35575f60d6d28b5b027ad6cd64981a4822fe632d508da3bd3c2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-14T15:58:55Z","title_canon_sha256":"3a3619696fedb4a34e92a2721f2b9e970921de75324f034c6d422377718a58ca"},"schema_version":"1.0","source":{"id":"2305.08190","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.08190","created_at":"2026-07-05T06:09:58Z"},{"alias_kind":"arxiv_version","alias_value":"2305.08190v1","created_at":"2026-07-05T06:09:58Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.08190","created_at":"2026-07-05T06:09:58Z"},{"alias_kind":"pith_short_12","alias_value":"C4HU3WSUK6DD","created_at":"2026-07-05T06:09:58Z"},{"alias_kind":"pith_short_16","alias_value":"C4HU3WSUK6DD2AV7","created_at":"2026-07-05T06:09:58Z"},{"alias_kind":"pith_short_8","alias_value":"C4HU3WSU","created_at":"2026-07-05T06:09:58Z"}],"graph_snapshots":[{"event_id":"sha256:47359771d7f30d80524e189610a9de4ad16868cd8685f78b3b777ef4a6bc74ca","target":"graph","created_at":"2026-07-05T06:09:58Z","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/2305.08190/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Predicting future motions of nearby agents is essential for an autonomous vehicle to take safe and effective actions. In this paper, we propose TSGN, a framework using Temporal Scene Graph Neural Networks with projected vectorized representations for multi-agent trajectory prediction. Projected vectorized representation models the traffic scene as a graph which is constructed by a set of vectors. These vectors represent agents, road network, and their spatial relative relationships. All relative features under this representation are both translationand rotation-invariant. Based on this repres","authors_text":"Bogdan Stanciulescu, Fabien Moutarde, Thomas Gilles, Yunong Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-14T15:58:55Z","title":"TSGN: Temporal Scene Graph Neural Networks with Projected Vectorized Representation for Multi-Agent Motion Prediction"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.08190","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":"sha256:9c6ae6453164dc0e8707f1d422996478a91f82fbc82483e42af563042afb5a0b","target":"record","created_at":"2026-07-05T06:09:58Z","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":"385d3fbc21c7a35575f60d6d28b5b027ad6cd64981a4822fe632d508da3bd3c2","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-14T15:58:55Z","title_canon_sha256":"3a3619696fedb4a34e92a2721f2b9e970921de75324f034c6d422377718a58ca"},"schema_version":"1.0","source":{"id":"2305.08190","kind":"arxiv","version":1}},"canonical_sha256":"170f4dda5457863d02bfb499d845d81f62e188d34e18bab3686d4078052dd1df","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"170f4dda5457863d02bfb499d845d81f62e188d34e18bab3686d4078052dd1df","first_computed_at":"2026-07-05T06:09:58.590512Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:09:58.590512Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1gtnHvcQPCDvCJAKpnKcfeqjXFUQaph6VlKLq7hsWbP67PiMRg6ZA6+MSw9EfxC6+9WnTpsMprC5mLO3IItJDw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:09:58.590905Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.08190","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9c6ae6453164dc0e8707f1d422996478a91f82fbc82483e42af563042afb5a0b","sha256:47359771d7f30d80524e189610a9de4ad16868cd8685f78b3b777ef4a6bc74ca"],"state_sha256":"f3b00c92afca6ed04ac118907faa0bf143c10025473527c2ad55f3469129d994"}