{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:OY3AV5A2HL6OZ677E3DHWUWYL7","short_pith_number":"pith:OY3AV5A2","canonical_record":{"source":{"id":"2002.06241","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-14T20:11:13Z","cross_cats_sorted":["cs.LG","cs.MA","cs.RO"],"title_canon_sha256":"6b6a21a9850e89bac92c2c6aea49233dc30a80a515381aba4107dd2feea64298","abstract_canon_sha256":"c676453f5a7c83a160da9c51b86df96bfc3fba6b41bf30b0784e910ad14cd27c"},"schema_version":"1.0"},"canonical_sha256":"76360af41a3afcecfbff26c67b52d85fdee79451eca9e1ec74bc1a7616c2cc09","source":{"kind":"arxiv","id":"2002.06241","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.06241","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"arxiv_version","alias_value":"2002.06241v1","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.06241","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_12","alias_value":"OY3AV5A2HL6O","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_16","alias_value":"OY3AV5A2HL6OZ677","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_8","alias_value":"OY3AV5A2","created_at":"2026-07-05T00:42:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:OY3AV5A2HL6OZ677E3DHWUWYL7","target":"record","payload":{"canonical_record":{"source":{"id":"2002.06241","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-14T20:11:13Z","cross_cats_sorted":["cs.LG","cs.MA","cs.RO"],"title_canon_sha256":"6b6a21a9850e89bac92c2c6aea49233dc30a80a515381aba4107dd2feea64298","abstract_canon_sha256":"c676453f5a7c83a160da9c51b86df96bfc3fba6b41bf30b0784e910ad14cd27c"},"schema_version":"1.0"},"canonical_sha256":"76360af41a3afcecfbff26c67b52d85fdee79451eca9e1ec74bc1a7616c2cc09","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:42:00.489246Z","signature_b64":"goR/h2sbmEv3wjsOwD4InDAXcddXz5uT+rqsWTLr29NYRe2w8lyXI6tAe+ZdMHVwSWT95sEjpjxcBQIWXXaCCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"76360af41a3afcecfbff26c67b52d85fdee79451eca9e1ec74bc1a7616c2cc09","last_reissued_at":"2026-07-05T00:42:00.488844Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:42:00.488844Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.06241","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":"2026-07-05T00:42:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"A+iEIMOKB11mgCvuQ7IxThHOpheyYEl96Xt8KO3st11M0obyOU4U6NZ0ZpxWufC+0YbxILjXDC6uS77xXvyCDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:32:25.040794Z"},"content_sha256":"e0200ed84736a0b249bb995f02441db2c9af5882b57964a18a9c3d032e97890c","schema_version":"1.0","event_id":"sha256:e0200ed84736a0b249bb995f02441db2c9af5882b57964a18a9c3d032e97890c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:OY3AV5A2HL6OZ677E3DHWUWYL7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.MA","cs.RO"],"primary_cat":"cs.CV","authors_text":"Hengbo Ma, Jiachen Li, Masayoshi Tomizuka, Zhihao Zhang","submitted_at":"2020-02-14T20:11:13Z","abstract_excerpt":"Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (like autonomous vehicles and social robots) to achieve safe and high-quality planning when they navigate in highly interactive and crowded scenarios. Due to the existence of frequent interactions and uncertainty in the scene evolution, it is desired for the prediction system to enable relational reasoning on different entities and provide a distribution of future trajectories for each agent. In this paper, we propose a generic generati"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.06241","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/2002.06241/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":"2026-07-05T00:42:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"glX9axu6JqB0cQwFnSinn/hRsGs1lrpH+UcA6YV1dJeHp8C3LmACSW2MsXEkgS/O5orTtjlmNXPXYK3gzkAgAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T06:32:25.041123Z"},"content_sha256":"30161999abf3349e20b908ee5d556fd2c92c9cd535ce54cffc503a63289c5aa1","schema_version":"1.0","event_id":"sha256:30161999abf3349e20b908ee5d556fd2c92c9cd535ce54cffc503a63289c5aa1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/bundle.json","state_url":"https://pith.science/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/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":"2026-08-05T06:32:25Z","links":{"resolver":"https://pith.science/pith/OY3AV5A2HL6OZ677E3DHWUWYL7","bundle":"https://pith.science/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/bundle.json","state":"https://pith.science/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OY3AV5A2HL6OZ677E3DHWUWYL7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:OY3AV5A2HL6OZ677E3DHWUWYL7","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":"c676453f5a7c83a160da9c51b86df96bfc3fba6b41bf30b0784e910ad14cd27c","cross_cats_sorted":["cs.LG","cs.MA","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-14T20:11:13Z","title_canon_sha256":"6b6a21a9850e89bac92c2c6aea49233dc30a80a515381aba4107dd2feea64298"},"schema_version":"1.0","source":{"id":"2002.06241","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.06241","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"arxiv_version","alias_value":"2002.06241v1","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.06241","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_12","alias_value":"OY3AV5A2HL6O","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_16","alias_value":"OY3AV5A2HL6OZ677","created_at":"2026-07-05T00:42:00Z"},{"alias_kind":"pith_short_8","alias_value":"OY3AV5A2","created_at":"2026-07-05T00:42:00Z"}],"graph_snapshots":[{"event_id":"sha256:30161999abf3349e20b908ee5d556fd2c92c9cd535ce54cffc503a63289c5aa1","target":"graph","created_at":"2026-07-05T00:42:00Z","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/2002.06241/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Effective understanding of the environment and accurate trajectory prediction of surrounding dynamic obstacles are indispensable for intelligent mobile systems (like autonomous vehicles and social robots) to achieve safe and high-quality planning when they navigate in highly interactive and crowded scenarios. Due to the existence of frequent interactions and uncertainty in the scene evolution, it is desired for the prediction system to enable relational reasoning on different entities and provide a distribution of future trajectories for each agent. In this paper, we propose a generic generati","authors_text":"Hengbo Ma, Jiachen Li, Masayoshi Tomizuka, Zhihao Zhang","cross_cats":["cs.LG","cs.MA","cs.RO"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-14T20:11:13Z","title":"Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.06241","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:e0200ed84736a0b249bb995f02441db2c9af5882b57964a18a9c3d032e97890c","target":"record","created_at":"2026-07-05T00:42:00Z","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":"c676453f5a7c83a160da9c51b86df96bfc3fba6b41bf30b0784e910ad14cd27c","cross_cats_sorted":["cs.LG","cs.MA","cs.RO"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2020-02-14T20:11:13Z","title_canon_sha256":"6b6a21a9850e89bac92c2c6aea49233dc30a80a515381aba4107dd2feea64298"},"schema_version":"1.0","source":{"id":"2002.06241","kind":"arxiv","version":1}},"canonical_sha256":"76360af41a3afcecfbff26c67b52d85fdee79451eca9e1ec74bc1a7616c2cc09","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"76360af41a3afcecfbff26c67b52d85fdee79451eca9e1ec74bc1a7616c2cc09","first_computed_at":"2026-07-05T00:42:00.488844Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:42:00.488844Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"goR/h2sbmEv3wjsOwD4InDAXcddXz5uT+rqsWTLr29NYRe2w8lyXI6tAe+ZdMHVwSWT95sEjpjxcBQIWXXaCCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:42:00.489246Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.06241","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e0200ed84736a0b249bb995f02441db2c9af5882b57964a18a9c3d032e97890c","sha256:30161999abf3349e20b908ee5d556fd2c92c9cd535ce54cffc503a63289c5aa1"],"state_sha256":"70fe84bfa38ad8bec1e97cd9608d007c086fdc5949380d754e3ccc6edd8fb107"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"N9vL3MwmnvI9pMykOPs9M3UYOfleiX/lQ8tY2k8RGkbfAXzEqRGxb2LxV8mORXLWywKvnIbWDlJRsueAexzHCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T06:32:25.044876Z","bundle_sha256":"8a3f788ed6c1294b518749d7b4ea13d1e068c54f786f78a7b002b47f1e5d8a32"}}