In this work, we explore the possibility of training high-parameter 3D Gaussian splatting (3DGS) models on large-scale, high-resolution datasets. We d...
3DGaussian Splatting (3DGS) has emerged as promising alternative in 3D representation. However, it still suffers from high training cost. This paper i...
3D Gaussian Splatting (3DGS) reconstructions are plagued by stubborn“floater”artifacts that degrade their geometric and visual fidelity. We are the fi...
The limitation of graphical user interface (GUI) data has been a significant barrier to the development of GUI agents today, especially for the deskto...
We introduce SEKI, a novel large language model (LLM)-based neural architecture search (NAS) method. Inspired by the chain-of-thought (CoT) paradigm i...
Large-scale alignment pipelines typically pair a policy model with a separately trained reward model whose parameters remain frozen during reinforceme...
The increasing context window size in large language models (LLMs) has improved their ability to handle complex, long-text tasks. However, as the conv...
Current Retrieval-Augmented Generation (RAG) systems concatenate and process numerous retrieved document chunks for prefill which requires a large vol...
We present a generative dialogue system capable of operating in a full-duplex manner, allowing for seamless interaction. It is based on a large langua...