{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:I3BB4HCX33RJSQC6VDTRZGBPHX","short_pith_number":"pith:I3BB4HCX","canonical_record":{"source":{"id":"2409.01971","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-03T15:15:49Z","cross_cats_sorted":[],"title_canon_sha256":"8ca4fee8d984dd183f2786e92ae4149ccc89d92f122711216d2256715b2d813b","abstract_canon_sha256":"e3acc376667fe44d441fb88f2438fceefa79e67d44b07a0d1b07ae4c5767cdf4"},"schema_version":"1.0"},"canonical_sha256":"46c21e1c57dee299405ea8e71c982f3dd286aa3133eb18ac521f461ef7c971fe","source":{"kind":"arxiv","id":"2409.01971","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.01971","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"arxiv_version","alias_value":"2409.01971v2","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.01971","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_12","alias_value":"I3BB4HCX33RJ","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_16","alias_value":"I3BB4HCX33RJSQC6","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_8","alias_value":"I3BB4HCX","created_at":"2026-07-05T09:58:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:I3BB4HCX33RJSQC6VDTRZGBPHX","target":"record","payload":{"canonical_record":{"source":{"id":"2409.01971","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-03T15:15:49Z","cross_cats_sorted":[],"title_canon_sha256":"8ca4fee8d984dd183f2786e92ae4149ccc89d92f122711216d2256715b2d813b","abstract_canon_sha256":"e3acc376667fe44d441fb88f2438fceefa79e67d44b07a0d1b07ae4c5767cdf4"},"schema_version":"1.0"},"canonical_sha256":"46c21e1c57dee299405ea8e71c982f3dd286aa3133eb18ac521f461ef7c971fe","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:58:59.640844Z","signature_b64":"EFhmkmOgVHAlAA8WDz4JlSLzuJYC7m0Ecw6hA3mq5QKeD3JXr0C/6lMGlTq26o0u629ycUoirvO1LnVS4hreCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"46c21e1c57dee299405ea8e71c982f3dd286aa3133eb18ac521f461ef7c971fe","last_reissued_at":"2026-07-05T09:58:59.640401Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:58:59.640401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.01971","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":"2026-07-05T09:58:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H2TjCFBmfJDQOYpLKCwB28/35/W18glgZ1ZmPDC6rH8F2jfCVyXxyMjXiWQUx/k/8i96qbd2ai3Kepr7uMF7DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T15:34:26.952977Z"},"content_sha256":"13e8e297db3a101b5dfdc1b898de8f2bf9b03adedd766815b293a62b73fa57c6","schema_version":"1.0","event_id":"sha256:13e8e297db3a101b5dfdc1b898de8f2bf9b03adedd766815b293a62b73fa57c6"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:I3BB4HCX33RJSQC6VDTRZGBPHX","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic Environments","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Markus Lienkamp, Nico Uhlemann, Tobias Simeon Mohr, Yipeng Zhou","submitted_at":"2024-09-03T15:15:49Z","abstract_excerpt":"This paper explores pedestrian trajectory prediction in urban traffic while focusing on both model accuracy and real-world applicability. While promising approaches exist, they often revolve around pedestrian datasets excluding traffic-related information, or resemble architectures that are either not real-time capable or robust. To address these limitations, we first introduce a dedicated benchmark based on Argoverse 2, specifically targeting pedestrians in traffic environments. Following this, we present Snapshot, a modular, feed-forward neural network that outperforms the current state of t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.01971","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/2409.01971/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":"2026-07-05T09:58:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SFQ6vRZIbXpQqrdKvtlW0nedmj1nQUjBsdJd9N6tpkN4pdW/n2ZbW694WZqbGH7atOZXu6Yt6JF1KVvwdnJhAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T15:34:26.953490Z"},"content_sha256":"ee0e65c796f12089cc2898dfd11e0fa016fe5c5b3eaea1644aadeab67dde832c","schema_version":"1.0","event_id":"sha256:ee0e65c796f12089cc2898dfd11e0fa016fe5c5b3eaea1644aadeab67dde832c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/bundle.json","state_url":"https://pith.science/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/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":"2026-08-14T15:34:26Z","links":{"resolver":"https://pith.science/pith/I3BB4HCX33RJSQC6VDTRZGBPHX","bundle":"https://pith.science/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/bundle.json","state":"https://pith.science/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/state.json","well_known_bundle":"https://pith.science/.well-known/pith/I3BB4HCX33RJSQC6VDTRZGBPHX/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:I3BB4HCX33RJSQC6VDTRZGBPHX","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":"e3acc376667fe44d441fb88f2438fceefa79e67d44b07a0d1b07ae4c5767cdf4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-03T15:15:49Z","title_canon_sha256":"8ca4fee8d984dd183f2786e92ae4149ccc89d92f122711216d2256715b2d813b"},"schema_version":"1.0","source":{"id":"2409.01971","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.01971","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"arxiv_version","alias_value":"2409.01971v2","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.01971","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_12","alias_value":"I3BB4HCX33RJ","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_16","alias_value":"I3BB4HCX33RJSQC6","created_at":"2026-07-05T09:58:59Z"},{"alias_kind":"pith_short_8","alias_value":"I3BB4HCX","created_at":"2026-07-05T09:58:59Z"}],"graph_snapshots":[{"event_id":"sha256:ee0e65c796f12089cc2898dfd11e0fa016fe5c5b3eaea1644aadeab67dde832c","target":"graph","created_at":"2026-07-05T09:58:59Z","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/2409.01971/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This paper explores pedestrian trajectory prediction in urban traffic while focusing on both model accuracy and real-world applicability. While promising approaches exist, they often revolve around pedestrian datasets excluding traffic-related information, or resemble architectures that are either not real-time capable or robust. To address these limitations, we first introduce a dedicated benchmark based on Argoverse 2, specifically targeting pedestrians in traffic environments. Following this, we present Snapshot, a modular, feed-forward neural network that outperforms the current state of t","authors_text":"Markus Lienkamp, Nico Uhlemann, Tobias Simeon Mohr, Yipeng Zhou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-03T15:15:49Z","title":"Snapshot: Towards Application-centered Models for Pedestrian Trajectory Prediction in Urban Traffic Environments"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.01971","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":"sha256:13e8e297db3a101b5dfdc1b898de8f2bf9b03adedd766815b293a62b73fa57c6","target":"record","created_at":"2026-07-05T09:58:59Z","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":"e3acc376667fe44d441fb88f2438fceefa79e67d44b07a0d1b07ae4c5767cdf4","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-09-03T15:15:49Z","title_canon_sha256":"8ca4fee8d984dd183f2786e92ae4149ccc89d92f122711216d2256715b2d813b"},"schema_version":"1.0","source":{"id":"2409.01971","kind":"arxiv","version":2}},"canonical_sha256":"46c21e1c57dee299405ea8e71c982f3dd286aa3133eb18ac521f461ef7c971fe","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"46c21e1c57dee299405ea8e71c982f3dd286aa3133eb18ac521f461ef7c971fe","first_computed_at":"2026-07-05T09:58:59.640401Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:58:59.640401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EFhmkmOgVHAlAA8WDz4JlSLzuJYC7m0Ecw6hA3mq5QKeD3JXr0C/6lMGlTq26o0u629ycUoirvO1LnVS4hreCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:58:59.640844Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.01971","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13e8e297db3a101b5dfdc1b898de8f2bf9b03adedd766815b293a62b73fa57c6","sha256:ee0e65c796f12089cc2898dfd11e0fa016fe5c5b3eaea1644aadeab67dde832c"],"state_sha256":"77c7960eca3fdc42707202d12d666d5cea2c7d3333ccf3f4ee70104afa6c68cd"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6J72KXXIawgf4OFm+r5S5i1J1vaf0YA5NH0vYVcjpnV8XlkMOpFmawi+pPdcU2iBI5LCH9pAnm2QYFjHdusuAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T15:34:26.959190Z","bundle_sha256":"e1cd57ccadb14940f95bd1f8be857f953e079638e80ab40ccb041d9a03a01b0c"}}