Overall, our method can generate high-fidelity, diverse, and multi-view consistent meshes from single-view wild images within 30 seconds, as shown in Figure 1. We conduct extensive experiments on various wild 2D images with different styles.

In this work, we study the performance of byte-level and subword-level autoregressive models when trained using a fixed compute budget.

The application of reinforcement learning (RL) involving interactions with individuals has grown significantly in recent years.

This paper introduces a novel approach using Large Language Models (LLMs) integrated into an agent framework for flexible and effective personal mobility generation. LLMs overcome the limitations of previous models by effectively processing semantic data and offering versatility in modeling various tasks.