works on

From the 1 of 13 linked papers with an AI index.

activity
20242026
collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2026

MusaCoder: Native GPU Kernel Generation with Full-Stack Training on Moore Threads GPU

Kun Cheng, Songshuo Lu, Sicong Liao +7

Native GPU kernel generation turns high-level tensor programs into executable, efficient low-level code. Existing Large Language Models (LLMs) struggle with this task, while execut…

cs.CV2026

ReorgGS: Equivalent Distribution Reorganization for 3D Gaussian Splatting

Luchao Wang, Kaimin Liao, Qian Ren +3

A converged 3D Gaussian Splatting (3DGS) model may approximate the target scene while remaining poorly parameterized for further optimization. We identify this failure mode as \emp…

cs.CV2026

UniSem: Generalizable Semantic 3D Reconstruction from Sparse Unposed Images

Guibiao Liao, Qian Ren, Kaimin Liao +4

Semantic-aware 3D reconstruction from sparse, unposed images remains challenging for feed-forward 3D Gaussian Splatting (3DGS). Existing methods often predict an over-complete set…

cs.CV2025

StableGS: A Floater-Free Framework for 3D Gaussian Splatting

Luchao Wang, Qian Ren, Kaimin Liao +3

3D Gaussian Splatting (3DGS) reconstructions are plagued by stubborn ``floater" artifacts that degrade their geometric and visual fidelity. We are the first to reveal the root caus…

cs.CV2025

URPO: A Unified Reward & Policy Optimization Framework for Large Language Models

Songshuo Lu, Hua Wang, Zhi Chen +1

Large-scale alignment pipelines typically pair a policy model with a separately trained reward model whose parameters remain frozen during reinforcement learning (RL). This separat…

cs.CV2024

TurboRAG: Accelerating Retrieval-Augmented Generation with Precomputed KV Caches for Chunked Text

Songshuo Lu, Hua Wang, Yutian Rong +2

Current Retrieval-Augmented Generation (RAG) systems concatenate and process numerous retrieved document chunks for prefill which requires a large volume of computation, therefore…