6 papers
Attribution-Guided and Coverage-Maximized Pruning for Structural MoE Compression
Yifu Ding, Jiacheng Wang, Ge Yang +4
Mixture-of-Experts (MoE) models scale compute efficiently, yet remain expensive to deploy due to their substantial memory footprint and inference overhead. Prior compression method…
MemCam: Memory-Augmented Camera Control for Consistent Video Generation
Xinhang Gao, Junlin Guan, Shuhan Luo +3
Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during l…
Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging
Lujun Li, Zhu Qiyuan, Jiacheng Wang +4
Mixture of Experts (MoE) LLMs face significant obstacles due to their massive parameter scale, which imposes memory, storage, and deployment challenges. Although recent expert merg…
RIGI: Rectifying Image-to-3D Generation Inconsistency via Uncertainty-aware Learning
Jiacheng Wang, Zhedong Zheng, Wei Xu +1
Given a single image of a target object, image-to-3D generation aims to reconstruct its texture and geometric shape. Recent methods often utilize intermediate media, such as multi-…
Hunyuan3D 1.0: A Unified Framework for Text-to-3D and Image-to-3D Generation
Xianghui Yang, Huiwen Shi, Bowen Zhang +20
While 3D generative models have greatly improved artists' workflows, the existing diffusion models for 3D generation suffer from slow generation and poor generalization. To address…
Unified Diffusion-Based Rigid and Non-Rigid Editing with Text and Image Guidance
Jiacheng Wang, Ping Liu, Wei Xu
Existing text-to-image editing methods tend to excel either in rigid or non-rigid editing but encounter challenges when combining both, resulting in misaligned outputs with the pro…