11 papers
SAEVerbalizer: Generating Explanations for Sparse Autoencoder Features via Representation Verbalization
Weihan Meng, Hongzhu Guo, Yi Jing +5
Sparse autoencoders (SAEs) are proposed to extract numerous features from large language model (LLM) representations, yet explaining these features still relies primarily on extern…
ProxyUp: Training-Free Proxy-Conditioned Video Generation for Controllable Dynamics
Zanwei Zhou, Jiazhong Cen, Jiemin Fang +7
Precise control over complex dynamics remains challenging for modern video generative models, as text prompts alone often cannot specify physically plausible, fine-grained motion a…
Text-Image Conditioned 3D Generation
Jiazhong Cen, Jiemin Fang, Sikuang Li +8
High-quality 3D assets are essential for VR/AR, industrial design, and entertainment, motivating growing interest in generative models that create 3D content from user prompts. Mos…
MoRe: Motion-aware Feed-forward 4D Reconstruction Transformer
Juntong Fang, Zequn Chen, Weiqi Zhang +4
Reconstructing dynamic 4D scenes remains challenging due to the presence of moving objects that corrupt camera pose estimation. Existing optimization methods alleviate this issue w…
NuiWorld: Exploring a Scalable Framework for End-to-End Controllable World Generation
Han-Hung Lee, Cheng-Yu Yang, Yu-Lun Liu +1
World generation is a fundamental capability for applications like video games, simulation, and robotics. However, existing approaches face three main obstacles: controllability, s…
Efficient and Robust Video Defense Framework against 3D-field Personalized Talking Face
Rui-qing Sun, Xingshan Yao, Tian Lan +6
State-of-the-art 3D-field video-referenced Talking Face Generation (TFG) methods synthesize high-fidelity personalized talking-face videos in real time by modeling 3D geometry and…