Filtered to multimodal models · clear filter
This paper introduces a new type of AI model called memory foundation models, which allows the model to learn and retain information internally, rather than relying on external memory modules. This could be useful for practitioners who want to build more efficient and flexible AI agents.
This paper introduces SenseNova-U1.5, a powerful AI model that can understand, reason about, and generate visual content without needing a separate text-to-image model. Practitioners might care because this model can be used to create complex visual content, such as images and videos, with high fidelity and accuracy.
This paper introduces Hunyuan3D-Buffalo 1.0, a unified model for 3D generation, understanding, and editing, and demonstrates its state-of-the-art performance on various benchmarks. Practitioners may care about this work because it provides a scalable framework for 3D modeling and editing tasks.
This paper introduces Puffin-World, a unified multimodal model that combines physics, geometry, and appearance to generate and interact with 3D worlds. Practitioners might care because it enables physically consistent and visually stable world generation for applications like world exploration and simulation.