arXiv (All)
open access
Large Language Models in Transportation Systems Management and Operations: From Text Reasoning to Multi-modal Decision Support
Transportation systems management and operations (TSMO) increasingly depends on timely interpretation of heterogeneous data, from various sensor streams, incident reports, traveler feedback, and visual observations. Large language models (LLMs), including emerging multi-modal large language models (
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Unraveling the cognitive patterns of Large Language Models through module communities#1075995
- EVOKE: Eliciting World Knowledge in Agents for Transferable Decision-Making#1142935
- A Large Language Model-Based Academic Advising Assistant for Engineering Technology Students#1054536
- Revisiting Complete Reasoning Traces for Post-Training#975163
- CWM: Controllable White-Box Meta-Prompting for Adaptive Retrieval-Augmented Generation and Reasoning Ability#1109276
Record · ID 1386293
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive