We propose NdLinear as a drop-in replacement for standard linear layers -- marking an important step toward next-generation neural architectures.
In this study, we propose a highly-consistent data synthesis pipeline to tackle this challenge.
Conditional Image Generation
Personalized Image Generation
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Imitation Learning (IL) holds great promise for enabling agile locomotion in embodied agents.
Recently, large language model (LLM) based text-to-speech (TTS) systems have gradually become the mainstream in the industry due to their high naturalness and powerful zero-shot voice cloning capabilities. Here, we introduce the IndexTTS system, which is mainly based on the XTTS and Tortoise model.
Such structured representation of task-relevant knowledge enables low-cost models to solve complex tasks effectively.
The refined monodepth is in turn guides stereo effectively at ill-posed regions.
Visual Simultaneous Localization and Mapping (VSLAM) research faces significant challenges due to fragmented toolchains, complex system configurations, and inconsistent evaluation methodologies.
In this paper, we introduce OctGPT, a novel multiscale autoregressive model for 3D shape generation that dramatically improves the efficiency and performance of prior 3D autoregressive approaches, while rivaling or surpassing state-of-the-art diffusion models.
The capacity for complex mathematical reasoning is a key benchmark for artificial intelligence.
In this work, we revisit GRPO from a reinforce-like algorithm perspective and analyze its core components.