{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:XTKJWJX2MBN364JXS2ORCTBO22","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":"c4148eb58c9db86126d880a9c3cbfaab2fc771326dbc25d6598dba3db89b8449","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T15:50:35Z","title_canon_sha256":"d4700b26ebf99f8ef38196e72351509b772c5a187b52cc372210ec262aeebbdc"},"schema_version":"1.0","source":{"id":"2402.07233","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.07233","created_at":"2026-07-05T07:44:03Z"},{"alias_kind":"arxiv_version","alias_value":"2402.07233v1","created_at":"2026-07-05T07:44:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.07233","created_at":"2026-07-05T07:44:03Z"},{"alias_kind":"pith_short_12","alias_value":"XTKJWJX2MBN3","created_at":"2026-07-05T07:44:03Z"},{"alias_kind":"pith_short_16","alias_value":"XTKJWJX2MBN364JX","created_at":"2026-07-05T07:44:03Z"},{"alias_kind":"pith_short_8","alias_value":"XTKJWJX2","created_at":"2026-07-05T07:44:03Z"}],"graph_snapshots":[{"event_id":"sha256:f3dc01177fb5e8c3ffff8a931aff37a6f15175e445bc750cdee9a5af95f4b9ec","target":"graph","created_at":"2026-07-05T07:44:03Z","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/2402.07233/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Natural language processing (NLP) is a key component of intelligent transportation systems (ITS), but it faces many challenges in the transportation domain, such as domain-specific knowledge and data, and multi-modal inputs and outputs. This paper presents TransGPT, a novel (multi-modal) large language model for the transportation domain, which consists of two independent variants: TransGPT-SM for single-modal data and TransGPT-MM for multi-modal data. TransGPT-SM is finetuned on a single-modal Transportation dataset (STD) that contains textual data from various sources in the transportation d","authors_text":"Fangxu Hu, Peng Wang, Wenjuan Han, Xiang Wei","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T15:50:35Z","title":"TransGPT: Multi-modal Generative Pre-trained Transformer for Transportation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.07233","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:cac4d1516e666f0c4be24d8165ddb28b42f992a12947244a52dbe88ca6d5785e","target":"record","created_at":"2026-07-05T07:44:03Z","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":"c4148eb58c9db86126d880a9c3cbfaab2fc771326dbc25d6598dba3db89b8449","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-02-11T15:50:35Z","title_canon_sha256":"d4700b26ebf99f8ef38196e72351509b772c5a187b52cc372210ec262aeebbdc"},"schema_version":"1.0","source":{"id":"2402.07233","kind":"arxiv","version":1}},"canonical_sha256":"bcd49b26fa605bbf7137969d114c2ed69b0c17a98e7c9650a2cbf6ea150e2804","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bcd49b26fa605bbf7137969d114c2ed69b0c17a98e7c9650a2cbf6ea150e2804","first_computed_at":"2026-07-05T07:44:03.072900Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:44:03.072900Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"A9Kg7jLmL0TaZiSLdBp1+SqsYbonvyoE7P7ywGwiQ0Mz9cbLfdY/3TxGBxn7w33vCCuAypn95z5PBmgrYikcBw==","signature_status":"signed_v1","signed_at":"2026-07-05T07:44:03.073300Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.07233","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:cac4d1516e666f0c4be24d8165ddb28b42f992a12947244a52dbe88ca6d5785e","sha256:f3dc01177fb5e8c3ffff8a931aff37a6f15175e445bc750cdee9a5af95f4b9ec"],"state_sha256":"685f504ad02b9cca55414aa5f0cf32f0465321f38a5dbfae7af2d86700440896"}