GitHub ThinklabSJTU/Bench2Drive [NeurIPS 2024 Datasets and Benchmarks Track] ClosedLoop E2E

Dataset And Benchmark Neurips 2025 Model. NeurIPS 2022 Model Zoo Datasets and Generative HyperRepresentations HSGAIML Previous editions of the Datasets and Benchmarks track were highly successful and continuously growing. If you are willing to self-nominate to serve as an AC for NeurIPS 2025, please fill in this form

Our dataset features video clips with a complete set of driving maneuvers, diverse multi-agent interplay, and rich open-world driving knowledge, laying a stepping stone for future world model development. NeurIPS 2025 Datasets & Benchmarks Track Call for Papers The NeurIPS Datasets and Benchmarks track serves as a venue for high-quality publications on highly valuable machine learning datasets and benchmarks crucial for the development and continuous improvement of machine learning methods

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For each self-nomination application for reviewing at NeurIPS 2025, we will consider the following criteria as relevant. NeurIPS 2025 Datasets & Benchmarks Track Call for Papers The NeurIPS Datasets and Benchmarks track serves as a venue for high-quality publications on highly valuable machine learning datasets and benchmarks crucial for the development and continuous improvement of machine learning methods Select Year: (2025) 2025 2023 2024 2022 2021 2020 2019 2018 2017 2016 2015 2014

Dataset And Benchmark Neurips 2024 Dataset Mira Sybila. We introduce DrivingDojo, the first dataset tailor-made for training interactive world models with complex driving dynamics Built on a minimally modified MM-DiT [10] architecture, UniVG seamlessly integrates diverse types of inputs, including text prompts, masks, and existing images, and is able to adapt to different tasks by adjusting its inputs.

NeurIPS Poster EHRSHOT An EHR Benchmark for FewShot Evaluation of Foundation Models. Select Year: (2025) 2025 2023 2024 2022 2021 2020 2019 2018 2017 2016 2015 2014 The affinity scores were computed using a text similarity model comparing the paper's text with the reviewer's past work on OpenReview.