ChatPlanner: A Large Language Model Framework for Personalized Public Transit Routing

arXiv:2606.15315 · cs.AI · Submitted 2026-06-13 · Read on arXiv

cs.AI

Submitted: 2026-06-13

Updated: 2026-09-06

Comments: Paper Accepted at Transportation Research Part C

Code: https://github.com/langchain-ai/langgraph

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• RAG — 93× in this paper · explained in 3 episodes
• Fine-Tuning — 43× in this paper · explained in 5 episodes
• Accuracy — 32× in this paper · explained in 1 episode
• Large Language Model — 14× in this paper
• Calibration — 9× in this paper · explained in 7 episodes
• Computational Tractability — 8× in this paper · explained in 2 episodes
• Core — 7× in this paper · explained in 2 episodes
• Objective Function — 6× in this paper · explained in 2 episodes
• Adam — 4× in this paper · explained in 2 episodes
• Data Augmentation — 4× in this paper · explained in 7 episodes
• Embeddings — 3× in this paper · explained in 2 episodes
• Route Validity — 3× in this paper
• Semantic Similarity — 3× in this paper · explained in 2 episodes
• Station Identification — 3× in this paper
• Timetable Accuracy — 3× in this paper
• Walking Completeness — 3× in this paper
• AUC — 2× in this paper · explained in 2 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Concordance Correlation Coefficient — 2× in this paper
• F1 Score — 2× in this paper · explained in 3 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• Retrieval-Augmented Generation (RAG) — 2× in this paper · explained in 16 episodes
• Robustness — 2× in this paper · explained in 5 episodes
• Schema-Guided Dialogue — 2× in this paper
• Verification — 2× in this paper · explained in 2 episodes
• Annotator Agreement — 1× in this paper · explained in 1 episode
• Area Under the ROC Curve — 1× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Attention Mechanism — 1× in this paper · explained in 3 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Expected Calibration Error — 1× in this paper
• Generalization — 1× in this paper · explained in 13 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hallucination — 1× in this paper · explained in 3 episodes
• In-Context Learning — 1× in this paper · explained in 4 episodes
• Inverted Generational Distance — 1× in this paper
• LLMs with Retrieval-Augmented Generation — 1× in this paper
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Mean Absolute Error — 1× in this paper
• Modular Architecture — 1× in this paper · explained in 4 episodes
• Ontology — 1× in this paper · explained in 2 episodes
• Parameter-Efficient Fine-Tuning — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Quantization — 1× in this paper · explained in 12 episodes
• Root Mean Square Error — 1× in this paper
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Symmetric Mean Absolute Percentage Error — 1× in this paper
• Systematic Bias — 1× in this paper · explained in 3 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transport for London — 1× in this paper

Sources

• On the Opportunities and Risks of Foundation Models
• Using Large Language Models in Public Transit Systems, San Antonio as a case study
• Leveraging Large Language Models for Enhancing Public Transit Services
• TraveLLM: Could you plan my new public transit route in face of a network disruption?
• Parameter-Efficient Fine-Tuning for Large Models: A Comprehensive Survey
• OpenAI GPT-5 System Card
• Qwen2.5 Technical Report

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