{"url":"/dataset/lmdrive","name":"LMDrive","full_name":"LMDrive Dataset","description_markdown":"LMDrive Dataset consists of 64K instruction-sensor-control data clips collected in the CARLA simulator, where each clip includes one navigation instruction, several notice instructions, a sequence of multi-modal multi-view sensor data, and control signals. The duration of the clip spans from 2 to 20 seconds.\r\n\r\nDataset details\r\n\r\n- data/: dataset folder, the entire dataset contains about 2T of data.\r\n\r\n- data/Town01: sub dataset folder, which only consists of the data folder for the Town01\r\n\r\n- data/Town02: sub dataset folder, which only consists of the data folder for the Town02\r\n\r\n- ...\r\n\r\n- dataset_index.txt: the data list for pretraining the vision encoder\r\n\r\n- navigation_instruction_list.txt: the data list for instruction finetuning\r\n\r\n- notice_instruction_list.json: the data list for instruction finetuning (optional if the notice instruction data is not engaged in the training)","description_withheld":null,"homepage":"https://huggingface.co/datasets/deepcs233/LMDrive","introduced_date":"2023-12-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/lmdrive-closed-loop-end-to-end-driving-with","title":"LMDrive: Closed-Loop End-to-End Driving with Large Language Models","first_author":"Hao Shao","url":null},"license":{"name":"apache-2.0","url":null},"modalities":[],"tasks":[],"languages":[],"variants":["LMDrive"],"data_loaders":[],"num_papers_in_archive":16,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}