Showing 4 open source projects for "car simulation source code"

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  • 1
    LingBot-World

    LingBot-World

    Advancing Open-source World Models

    LingBot-World is an open-source, high-fidelity world simulator designed to advance the state of world models through video generation. Built on top of Wan2.2, it enables realistic, dynamic environment simulation across diverse styles, including real-world, scientific, and stylized domains. LingBot-World supports long-term temporal consistency, maintaining coherent scenes and interactions over minute-level horizons.
    Downloads: 5 This Week
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  • 2
    AICGSecEval

    AICGSecEval

    A.S.E (AICGSecEval) is a repository-level AI-generated code security

    AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development...
    Downloads: 0 This Week
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  • 3
    Google DeepMind GraphCast and GenCast

    Google DeepMind GraphCast and GenCast

    Global weather forecasting model using graph neural networks and JAX

    GraphCast, developed by Google DeepMind, is a research-grade weather forecasting framework that employs graph neural networks (GNNs) to generate medium-range global weather predictions. The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with...
    Downloads: 3 This Week
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  • 4
    Automated Interpretability

    Automated Interpretability

    Code for Language models can explain neurons in language models paper

    The automated-interpretability repository implements tools and pipelines for automatically generating, simulating, and scoring explanations of neuron (or latent feature) behavior in neural networks. Instead of relying purely on manual, ad hoc interpretability probing, this repo aims to scale interpretability by using algorithmic methods that produce candidate explanations and assess their quality. It includes a “neuron explainer” component that, given a target neuron or latent feature,...
    Downloads: 0 This Week
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