{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:QGO34QRS4GHYAMPV7B5H5PU5IY","short_pith_number":"pith:QGO34QRS","canonical_record":{"source":{"id":"2301.07103","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-16T09:54:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"17df8cf2259e2fcd6f57cf1840497e2c1cf5bce3a800dac2ebcadc9569db9b8a","abstract_canon_sha256":"b5f9bc72c5ca047f4861ef8d9073d2b9ffb5175c526378661c68aefbca5bd8cb"},"schema_version":"1.0"},"canonical_sha256":"819dbe4232e18f8031f5f87a7ebe9d46090d765be24992dedfe282dbf45fa0e6","source":{"kind":"arxiv","id":"2301.07103","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.07103","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"arxiv_version","alias_value":"2301.07103v1","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.07103","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_12","alias_value":"QGO34QRS4GHY","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_16","alias_value":"QGO34QRS4GHYAMPV","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_8","alias_value":"QGO34QRS","created_at":"2026-07-05T05:34:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:QGO34QRS4GHYAMPV7B5H5PU5IY","target":"record","payload":{"canonical_record":{"source":{"id":"2301.07103","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-16T09:54:02Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"17df8cf2259e2fcd6f57cf1840497e2c1cf5bce3a800dac2ebcadc9569db9b8a","abstract_canon_sha256":"b5f9bc72c5ca047f4861ef8d9073d2b9ffb5175c526378661c68aefbca5bd8cb"},"schema_version":"1.0"},"canonical_sha256":"819dbe4232e18f8031f5f87a7ebe9d46090d765be24992dedfe282dbf45fa0e6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:34:05.595039Z","signature_b64":"fQmKt5BTfZQw7nOV2hAa6NwakxArPVSFWC8Lw6SEEmMLwrWP1Uh6uYjZkPxSlQ/AKsuflXb+0HiZFDpneQOPAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"819dbe4232e18f8031f5f87a7ebe9d46090d765be24992dedfe282dbf45fa0e6","last_reissued_at":"2026-07-05T05:34:05.594568Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:34:05.594568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.07103","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":"2026-07-05T05:34:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UWBPTyw3hxsCa8PQR7kzNBgw6C6EiJwjjaU+1SuD0SL+KCAYHzANIKMW8sW7tnw8LccZxtJIMqtGCuVszky0Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T11:25:01.869304Z"},"content_sha256":"1b4c978475b81528958c60f0c039c34858f3d5bb16d361f49b0b79eae8895be4","schema_version":"1.0","event_id":"sha256:1b4c978475b81528958c60f0c039c34858f3d5bb16d361f49b0b79eae8895be4"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:QGO34QRS4GHYAMPV7B5H5PU5IY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Continuous Trajectory Generation Based on Two-Stage GAN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Jiawei Jiang, Jingyuan Wang, Wayne Xin Zhao, Wenjun Jiang","submitted_at":"2023-01-16T09:54:02Z","abstract_excerpt":"Simulating the human mobility and generating large-scale trajectories are of great use in many real-world applications, such as urban planning, epidemic spreading analysis, and geographic privacy protect. Although many previous works have studied the problem of trajectory generation, the continuity of the generated trajectories has been neglected, which makes these methods useless for practical urban simulation scenarios. To solve this problem, we propose a novel two-stage generative adversarial framework to generate the continuous trajectory on the road network, namely TS-TrajGen, which effic"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.07103","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/2301.07103/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":"2026-07-05T05:34:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kY/z4QWVl+7kRO4MFlhOHgQwYUICjUR9O9sN5W/hhjlFzYCDvljInGbHzwMcC7niPSSDAt5853g7Vq4yzHAZCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-23T11:25:01.870088Z"},"content_sha256":"2de43c9f65e7cd440fcb2f143dbeca8ec349d6beff1a042a4f4dc362e9a9b59b","schema_version":"1.0","event_id":"sha256:2de43c9f65e7cd440fcb2f143dbeca8ec349d6beff1a042a4f4dc362e9a9b59b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/bundle.json","state_url":"https://pith.science/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/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":"2026-08-23T11:25:01Z","links":{"resolver":"https://pith.science/pith/QGO34QRS4GHYAMPV7B5H5PU5IY","bundle":"https://pith.science/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/bundle.json","state":"https://pith.science/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QGO34QRS4GHYAMPV7B5H5PU5IY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:QGO34QRS4GHYAMPV7B5H5PU5IY","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":"b5f9bc72c5ca047f4861ef8d9073d2b9ffb5175c526378661c68aefbca5bd8cb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-16T09:54:02Z","title_canon_sha256":"17df8cf2259e2fcd6f57cf1840497e2c1cf5bce3a800dac2ebcadc9569db9b8a"},"schema_version":"1.0","source":{"id":"2301.07103","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.07103","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"arxiv_version","alias_value":"2301.07103v1","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.07103","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_12","alias_value":"QGO34QRS4GHY","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_16","alias_value":"QGO34QRS4GHYAMPV","created_at":"2026-07-05T05:34:05Z"},{"alias_kind":"pith_short_8","alias_value":"QGO34QRS","created_at":"2026-07-05T05:34:05Z"}],"graph_snapshots":[{"event_id":"sha256:2de43c9f65e7cd440fcb2f143dbeca8ec349d6beff1a042a4f4dc362e9a9b59b","target":"graph","created_at":"2026-07-05T05:34:05Z","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/2301.07103/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Simulating the human mobility and generating large-scale trajectories are of great use in many real-world applications, such as urban planning, epidemic spreading analysis, and geographic privacy protect. Although many previous works have studied the problem of trajectory generation, the continuity of the generated trajectories has been neglected, which makes these methods useless for practical urban simulation scenarios. To solve this problem, we propose a novel two-stage generative adversarial framework to generate the continuous trajectory on the road network, namely TS-TrajGen, which effic","authors_text":"Jiawei Jiang, Jingyuan Wang, Wayne Xin Zhao, Wenjun Jiang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-16T09:54:02Z","title":"Continuous Trajectory Generation Based on Two-Stage GAN"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.07103","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":"sha256:1b4c978475b81528958c60f0c039c34858f3d5bb16d361f49b0b79eae8895be4","target":"record","created_at":"2026-07-05T05:34:05Z","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":"b5f9bc72c5ca047f4861ef8d9073d2b9ffb5175c526378661c68aefbca5bd8cb","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-01-16T09:54:02Z","title_canon_sha256":"17df8cf2259e2fcd6f57cf1840497e2c1cf5bce3a800dac2ebcadc9569db9b8a"},"schema_version":"1.0","source":{"id":"2301.07103","kind":"arxiv","version":1}},"canonical_sha256":"819dbe4232e18f8031f5f87a7ebe9d46090d765be24992dedfe282dbf45fa0e6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"819dbe4232e18f8031f5f87a7ebe9d46090d765be24992dedfe282dbf45fa0e6","first_computed_at":"2026-07-05T05:34:05.594568Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:34:05.594568Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"fQmKt5BTfZQw7nOV2hAa6NwakxArPVSFWC8Lw6SEEmMLwrWP1Uh6uYjZkPxSlQ/AKsuflXb+0HiZFDpneQOPAA==","signature_status":"signed_v1","signed_at":"2026-07-05T05:34:05.595039Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.07103","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b4c978475b81528958c60f0c039c34858f3d5bb16d361f49b0b79eae8895be4","sha256:2de43c9f65e7cd440fcb2f143dbeca8ec349d6beff1a042a4f4dc362e9a9b59b"],"state_sha256":"f5eb9cc8fc149ac89588fc28237d87af7f9b792557422e812d136252ae1eaee4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xI0czHY2F4MZ8TFr0B3ipXOEohpVwjhW1GgX0gAiyDZXiX0NS8GgDIs2Si/5AMsLEHY6bXd+ckJ/+FVlCmBOBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-23T11:25:01.876343Z","bundle_sha256":"0fae5726a4983d7c920f6d924f338982fd44aa74a41945913e11118456b680f4"}}