{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:5LA62VW45ISOJZ6I6SSKBM6ZC4","short_pith_number":"pith:5LA62VW4","canonical_record":{"source":{"id":"2409.14516","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-09-22T16:20:00Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"220b7984dc383a348e351374c2c64924bfe89ac5f1dce5278ed48b4b3e4fa71a","abstract_canon_sha256":"9516f4e5d4d75c87322a36d5470eb48acf0f4e809284f2ba2fb549f983a3d190"},"schema_version":"1.0"},"canonical_sha256":"eac1ed56dcea24e4e7c8f4a4a0b3d9172f1665b8c78bb0bd1050e2af992a9efa","source":{"kind":"arxiv","id":"2409.14516","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.14516","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"arxiv_version","alias_value":"2409.14516v1","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.14516","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_12","alias_value":"5LA62VW45ISO","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_16","alias_value":"5LA62VW45ISOJZ6I","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_8","alias_value":"5LA62VW4","created_at":"2026-07-05T09:10:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:5LA62VW45ISOJZ6I6SSKBM6ZC4","target":"record","payload":{"canonical_record":{"source":{"id":"2409.14516","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-09-22T16:20:00Z","cross_cats_sorted":["cs.CL","cs.IR"],"title_canon_sha256":"220b7984dc383a348e351374c2c64924bfe89ac5f1dce5278ed48b4b3e4fa71a","abstract_canon_sha256":"9516f4e5d4d75c87322a36d5470eb48acf0f4e809284f2ba2fb549f983a3d190"},"schema_version":"1.0"},"canonical_sha256":"eac1ed56dcea24e4e7c8f4a4a0b3d9172f1665b8c78bb0bd1050e2af992a9efa","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:10:17.835034Z","signature_b64":"Lrl2ySpjqktRrc0q/tGJIOMBd25jEzleZ4Pid9B4MqxsmROuI1ZgfJ0upgK0/20oEgYbybuVa3lzpNbl/Hq1DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eac1ed56dcea24e4e7c8f4a4a0b3d9172f1665b8c78bb0bd1050e2af992a9efa","last_reissued_at":"2026-07-05T09:10:17.834546Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:10:17.834546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2409.14516","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":"2026-07-05T09:10:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"/9BGPBYuyUP7JXP1GUazr/zwUdQAPvvNu8OadWEDFXNIAUQyBDwNuzsqajD8OXp8ySFzr3LWGY+1vT7dpv6HDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T23:01:15.303359Z"},"content_sha256":"e85734f40799d8c190f5237e321f89ee7bda6aa6b5177b9d1ee282f1d37ad6ae","schema_version":"1.0","event_id":"sha256:e85734f40799d8c190f5237e321f89ee7bda6aa6b5177b9d1ee282f1d37ad6ae"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:5LA62VW45ISOJZ6I6SSKBM6ZC4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Words: Evaluating Large Language Models in Transportation Planning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.IR"],"primary_cat":"cs.AI","authors_text":"Manzhu Yu, Shaowei Ying, Zhenlong Li","submitted_at":"2024-09-22T16:20:00Z","abstract_excerpt":"The resurgence and rapid advancement of Generative Artificial Intelligence (GenAI) in 2023 has catalyzed transformative shifts across numerous industry sectors, including urban transportation and logistics. This study investigates the evaluation of Large Language Models (LLMs), specifically GPT-4 and Phi-3-mini, to enhance transportation planning. The study assesses the performance and spatial comprehension of these models through a transportation-informed evaluation framework that includes general geospatial skills, general transportation domain skills, and real-world transportation problem-s"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.14516","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/2409.14516/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":"2026-07-05T09:10:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xeFtJJA/e9uGIbXQb/3L7LuFqlgwuC9q1R9aWdX8G5R70kZhykTyT+EYT65N0SGMzo4a2NriWIhiDh/k5qonBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T23:01:15.303748Z"},"content_sha256":"4a6cb872c068e958a204eb0525d640f6387bde66c258937c69c23bc93d3eb347","schema_version":"1.0","event_id":"sha256:4a6cb872c068e958a204eb0525d640f6387bde66c258937c69c23bc93d3eb347"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/bundle.json","state_url":"https://pith.science/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/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":"2026-08-03T23:01:15Z","links":{"resolver":"https://pith.science/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4","bundle":"https://pith.science/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/bundle.json","state":"https://pith.science/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5LA62VW45ISOJZ6I6SSKBM6ZC4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:5LA62VW45ISOJZ6I6SSKBM6ZC4","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":"9516f4e5d4d75c87322a36d5470eb48acf0f4e809284f2ba2fb549f983a3d190","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-09-22T16:20:00Z","title_canon_sha256":"220b7984dc383a348e351374c2c64924bfe89ac5f1dce5278ed48b4b3e4fa71a"},"schema_version":"1.0","source":{"id":"2409.14516","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.14516","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"arxiv_version","alias_value":"2409.14516v1","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.14516","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_12","alias_value":"5LA62VW45ISO","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_16","alias_value":"5LA62VW45ISOJZ6I","created_at":"2026-07-05T09:10:17Z"},{"alias_kind":"pith_short_8","alias_value":"5LA62VW4","created_at":"2026-07-05T09:10:17Z"}],"graph_snapshots":[{"event_id":"sha256:4a6cb872c068e958a204eb0525d640f6387bde66c258937c69c23bc93d3eb347","target":"graph","created_at":"2026-07-05T09:10:17Z","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/2409.14516/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The resurgence and rapid advancement of Generative Artificial Intelligence (GenAI) in 2023 has catalyzed transformative shifts across numerous industry sectors, including urban transportation and logistics. This study investigates the evaluation of Large Language Models (LLMs), specifically GPT-4 and Phi-3-mini, to enhance transportation planning. The study assesses the performance and spatial comprehension of these models through a transportation-informed evaluation framework that includes general geospatial skills, general transportation domain skills, and real-world transportation problem-s","authors_text":"Manzhu Yu, Shaowei Ying, Zhenlong Li","cross_cats":["cs.CL","cs.IR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-09-22T16:20:00Z","title":"Beyond Words: Evaluating Large Language Models in Transportation Planning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.14516","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:e85734f40799d8c190f5237e321f89ee7bda6aa6b5177b9d1ee282f1d37ad6ae","target":"record","created_at":"2026-07-05T09:10:17Z","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":"9516f4e5d4d75c87322a36d5470eb48acf0f4e809284f2ba2fb549f983a3d190","cross_cats_sorted":["cs.CL","cs.IR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-09-22T16:20:00Z","title_canon_sha256":"220b7984dc383a348e351374c2c64924bfe89ac5f1dce5278ed48b4b3e4fa71a"},"schema_version":"1.0","source":{"id":"2409.14516","kind":"arxiv","version":1}},"canonical_sha256":"eac1ed56dcea24e4e7c8f4a4a0b3d9172f1665b8c78bb0bd1050e2af992a9efa","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eac1ed56dcea24e4e7c8f4a4a0b3d9172f1665b8c78bb0bd1050e2af992a9efa","first_computed_at":"2026-07-05T09:10:17.834546Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:10:17.834546Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Lrl2ySpjqktRrc0q/tGJIOMBd25jEzleZ4Pid9B4MqxsmROuI1ZgfJ0upgK0/20oEgYbybuVa3lzpNbl/Hq1DA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:10:17.835034Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.14516","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e85734f40799d8c190f5237e321f89ee7bda6aa6b5177b9d1ee282f1d37ad6ae","sha256:4a6cb872c068e958a204eb0525d640f6387bde66c258937c69c23bc93d3eb347"],"state_sha256":"00a254c1042d4cab766275bdf85f855f9259ee15c7b6aa391563068c1a0c67a2"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FBizkoIKJ/SREjC/oDD/1fWaOtEzJDU+DYWLbVbk41NdNAt73R3XN9IVpSM+wfSOdjiYOdo8b80HlOI94G1DCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T23:01:15.306877Z","bundle_sha256":"9bf88661b86317fcee64f598a7f70c922723e853a771995ec3d7a92a990cd96d"}}