TransCity VLM Dataset The TransCity VLM Dataset provides multimodal smart city data for traffic, energy, mobility, grid operation, urban context understanding, and map grounded question answering. It supports the training and evaluation of vision language models for urban prediction, decision support, conversational QA, and reasoning tasks. The training data are available at this Hugging Face dataset repository. Dataset Summary Split Rows / Files : test JSONL rows 308,642 large scale QA rows 101,736 multi turn QA rows 138,558 COT QA rows 37,713 map screenshot files 28,055 Dataset Components Component Content Typical use test/ Forecasting style JSONL records for traffic and energy domains across multiple regions and time windows. Checkpoint evaluation and reproducibility. qa large scale/ Single turn QA records covering traffic, energy, bus mobility, grid operation, site context, relevance, and explanation tasks. Instruction tuning and QA training. qa multi turn/ Multi turn smart city dialogues spanning traffic, energy, bus, grid, and urban context tasks. Dialogue modeling and conversational QA training. qa cot/ QA records with reasoning traces for prediction, explanation, relevance,…
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