{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:MQM3Y6HWT4LISDHYPUYBHND4ZV","short_pith_number":"pith:MQM3Y6HW","canonical_record":{"source":{"id":"2605.30014","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T14:39:40Z","cross_cats_sorted":[],"title_canon_sha256":"0bc3a0dfef5a9d0e9ce9add8ab76182cda9abbe6349153a75f230b5b8d1a574b","abstract_canon_sha256":"6eb8ee2e50048e9f651fb4692f2c04035b603b525e10b9d42cb0cc0fefa69845"},"schema_version":"1.0"},"canonical_sha256":"6419bc78f69f16890cf87d3013b47ccd79e767cbdbb5a66d771217fd783c9831","source":{"kind":"arxiv","id":"2605.30014","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30014","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30014v1","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30014","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_12","alias_value":"MQM3Y6HWT4LI","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_16","alias_value":"MQM3Y6HWT4LISDHY","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_8","alias_value":"MQM3Y6HW","created_at":"2026-05-29T02:06:07Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:MQM3Y6HWT4LISDHYPUYBHND4ZV","target":"record","payload":{"canonical_record":{"source":{"id":"2605.30014","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T14:39:40Z","cross_cats_sorted":[],"title_canon_sha256":"0bc3a0dfef5a9d0e9ce9add8ab76182cda9abbe6349153a75f230b5b8d1a574b","abstract_canon_sha256":"6eb8ee2e50048e9f651fb4692f2c04035b603b525e10b9d42cb0cc0fefa69845"},"schema_version":"1.0"},"canonical_sha256":"6419bc78f69f16890cf87d3013b47ccd79e767cbdbb5a66d771217fd783c9831","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-29T02:06:07.005884Z","signature_b64":"wXQ6PNFPUvuNgargcejhg0Tc5YbOO+UWcr+ODLun8O1NBi44j7+BqIv9MMOZKxUy46wos0LYeqHwbqongi3RDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6419bc78f69f16890cf87d3013b47ccd79e767cbdbb5a66d771217fd783c9831","last_reissued_at":"2026-05-29T02:06:07.005036Z","signature_status":"signed_v1","first_computed_at":"2026-05-29T02:06:07.005036Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2605.30014","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":"2026-05-29T02:06:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"paJNoqzyhPz9xUsrBhAuN1lG9OM84nosDZ7n+jklax/lNhXwl6bPqroXRfMGnIzCSeQVSt3KVY4JO9TlwE8sCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T01:11:50.041534Z"},"content_sha256":"9298a9362b2a65ee3a111eda214fa37a855dcc51720c8ba1a800865804401943","schema_version":"1.0","event_id":"sha256:9298a9362b2a65ee3a111eda214fa37a855dcc51720c8ba1a800865804401943"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:MQM3Y6HWT4LISDHYPUYBHND4ZV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"From GPS Points to Travel Patterns: Flexible and Semantic Trajectory Generation with LLMs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Chenhao Wang, Lisi Chen, Panos Kalnis, Shuo Shang, Silin Zhou, Yuntao Wen","submitted_at":"2026-05-28T14:39:40Z","abstract_excerpt":"Urban trajectories play a crucial role in modeling urban dynamics and supporting various smart city applications. However, privacy concerns restrict access to large-scale and high-quality trajectory datasets. Trajectory generation provides a promising alternative by synthesizing realistic data to mitigate privacy risks. However, existing methods fail to explicitly capture travel patterns and can only generate fixed-length trajectories under a single condition. To address these limitations, we propose \\textbf{HTP}, which \\textbf{H}ierarchically generates \\textbf{T}ravel patterns first and then "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30014","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/2605.30014/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":"2026-05-29T02:06:07Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fGSnCbOULAdpJnso4GhiHkw95emL+bPqawkMkli18RafeHBXlrOpgWIYRlby27q22eJx7mTwMLmLfcfXKZyVCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-11T01:11:50.042303Z"},"content_sha256":"2fa5022bbac2ca55244340ca8562122ff384d481299a07ca828831de21d9e535","schema_version":"1.0","event_id":"sha256:2fa5022bbac2ca55244340ca8562122ff384d481299a07ca828831de21d9e535"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/bundle.json","state_url":"https://pith.science/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/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":"2026-06-11T01:11:50Z","links":{"resolver":"https://pith.science/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV","bundle":"https://pith.science/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/bundle.json","state":"https://pith.science/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MQM3Y6HWT4LISDHYPUYBHND4ZV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:MQM3Y6HWT4LISDHYPUYBHND4ZV","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":"6eb8ee2e50048e9f651fb4692f2c04035b603b525e10b9d42cb0cc0fefa69845","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T14:39:40Z","title_canon_sha256":"0bc3a0dfef5a9d0e9ce9add8ab76182cda9abbe6349153a75f230b5b8d1a574b"},"schema_version":"1.0","source":{"id":"2605.30014","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2605.30014","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"arxiv_version","alias_value":"2605.30014v1","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2605.30014","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_12","alias_value":"MQM3Y6HWT4LI","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_16","alias_value":"MQM3Y6HWT4LISDHY","created_at":"2026-05-29T02:06:07Z"},{"alias_kind":"pith_short_8","alias_value":"MQM3Y6HW","created_at":"2026-05-29T02:06:07Z"}],"graph_snapshots":[{"event_id":"sha256:2fa5022bbac2ca55244340ca8562122ff384d481299a07ca828831de21d9e535","target":"graph","created_at":"2026-05-29T02:06:07Z","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/2605.30014/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Urban trajectories play a crucial role in modeling urban dynamics and supporting various smart city applications. However, privacy concerns restrict access to large-scale and high-quality trajectory datasets. Trajectory generation provides a promising alternative by synthesizing realistic data to mitigate privacy risks. However, existing methods fail to explicitly capture travel patterns and can only generate fixed-length trajectories under a single condition. To address these limitations, we propose \\textbf{HTP}, which \\textbf{H}ierarchically generates \\textbf{T}ravel patterns first and then ","authors_text":"Chenhao Wang, Lisi Chen, Panos Kalnis, Shuo Shang, Silin Zhou, Yuntao Wen","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T14:39:40Z","title":"From GPS Points to Travel Patterns: Flexible and Semantic Trajectory Generation with LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2605.30014","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":"sha256:9298a9362b2a65ee3a111eda214fa37a855dcc51720c8ba1a800865804401943","target":"record","created_at":"2026-05-29T02:06:07Z","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":"6eb8ee2e50048e9f651fb4692f2c04035b603b525e10b9d42cb0cc0fefa69845","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AI","submitted_at":"2026-05-28T14:39:40Z","title_canon_sha256":"0bc3a0dfef5a9d0e9ce9add8ab76182cda9abbe6349153a75f230b5b8d1a574b"},"schema_version":"1.0","source":{"id":"2605.30014","kind":"arxiv","version":1}},"canonical_sha256":"6419bc78f69f16890cf87d3013b47ccd79e767cbdbb5a66d771217fd783c9831","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6419bc78f69f16890cf87d3013b47ccd79e767cbdbb5a66d771217fd783c9831","first_computed_at":"2026-05-29T02:06:07.005036Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-29T02:06:07.005036Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"wXQ6PNFPUvuNgargcejhg0Tc5YbOO+UWcr+ODLun8O1NBi44j7+BqIv9MMOZKxUy46wos0LYeqHwbqongi3RDg==","signature_status":"signed_v1","signed_at":"2026-05-29T02:06:07.005884Z","signed_message":"canonical_sha256_bytes"},"source_id":"2605.30014","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9298a9362b2a65ee3a111eda214fa37a855dcc51720c8ba1a800865804401943","sha256:2fa5022bbac2ca55244340ca8562122ff384d481299a07ca828831de21d9e535"],"state_sha256":"0555a381d9b3bf8b5c4317b4d76976a8e21771391843f0dff0899fc3af9d9069"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6Yy+bBt9HmV2NRrLTKyFKUFyWhaHx3U5M9lwSuzCRnurqzsjVAZcoYMZZsTTggXNxGfIdtb9rK670Hnuvp8kDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-11T01:11:50.046357Z","bundle_sha256":"9d78824d5b102154f4e6e4386f63510c2da65b7d0ae5423cc6ba7b8b6845d9bc"}}