4 projects for "dynamic process simulation" with 2 filters applied:

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  • 1
    Lyra 2

    Lyra 2

    Project Lyra: Open Generative 3D World Models

    ...The system evolves across versions, with newer iterations introducing long-horizon generation and improved 3D consistency across frames. It combines elements of computer vision, generative modeling, and spatial intelligence to produce dynamic and navigable virtual worlds. The architecture is designed to handle both 3D and 4D scene generation, making it suitable for applications such as simulation, gaming, and virtual environments. By emphasizing open implementations, the project provides researchers and developers with access to cutting-edge generative modeling techniques.
    Downloads: 2 This Week
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  • 2
    MiniMax-01

    MiniMax-01

    Large-language-model & vision-language-model based on Linear Attention

    ...It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel strategies such as LASP+, varlen ring attention, and Expert Tensor Parallelism, enabling a training context of 1 million tokens and up to 4 million tokens at inference. MiniMax-VL-01 extends this core by adding a 303M-parameter Vision Transformer and a two-layer MLP projector in a ViT–MLP–LLM framework, allowing the model to process images at dynamic resolutions up to 2016×2016.
    Downloads: 0 This Week
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  • 3
    HY-World 2.0

    HY-World 2.0

    A Multi-Modal World Model for Reconstructing, Generating, Simulation

    HY-World 2.0 is a multi-modal world model framework for reconstructing, generating, and simulating navigable 3D worlds from diverse inputs. It accepts text prompts, single-view images, multi-view images, and videos, and produces 3D world representations rather than limiting output to flat video generation. For text and single-image inputs, it generates high-fidelity 3D Gaussian Splatting scenes through a multi-stage pipeline that includes panorama generation, trajectory planning, world...
    Downloads: 1 This Week
    Last Update:
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  • 4
    MiniMax-M2.7

    MiniMax-M2.7

    Self-evolving AI model for agents, coding, and complex workflows

    MiniMax-M2.7 is a large-scale open-weight language model designed for advanced agent-based workflows, professional software engineering, and complex productivity tasks. With 229B parameters, it introduces a self-evolution framework in which the model actively improves its own capabilities by updating memory, generating skills, and iterating through reinforcement learning experiments. This process enables it to autonomously refine systems, achieving measurable performance gains such as a 30%...
    Downloads: 0 This Week
    Last Update:
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