32 citations · 89 across the 10 of their papers we have counts for
10 papers
SeedPolicy: Horizon Scaling via Self-Evolving Diffusion Policy for Robot Manipulation
Youqiang Gui, Yuxuan Zhou, Shen Cheng +4
Imitation Learning (IL) enables robots to acquire manipulation skills from expert demonstrations. Diffusion Policy (DP) models multi-modal expert behaviors but degrades when naivel…
Balancing Diversity and Risk in LLM Sampling: How to Select Your Method and Parameter for Open-Ended Text Generation
Yuxuan Zhou, Margret Keuper, Mario Fritz
Sampling-based decoding strategies have been widely adopted for Large Language Models (LLMs) in numerous applications, targeting a balance between diversity and quality via tempera…
MultiMax: Sparse and Multi-Modal Attention Learning
Yuxuan Zhou, Mario Fritz, Margret Keuper
SoftMax is a ubiquitous ingredient of modern machine learning algorithms. It maps an input vector onto a probability simplex and reweights the input by concentrating the probabilit…
BOTH2Hands: Inferring 3D Hands from Both Text Prompts and Body Dynamics
Wenqian Zhang, Molin Huang, Yuxuan Zhou +4
The recently emerging text-to-motion advances have spired numerous attempts for convenient and interactive human motion generation. Yet, existing methods are largely limited to gen…
Local Spherical Harmonics Improve Skeleton-Based Hand Action Recognition
Katharina Prasse, Steffen Jung, Yuxuan Zhou +1
Hand action recognition is essential. Communication, human-robot interactions, and gesture control are dependent on it. Skeleton-based action recognition traditionally includes han…
Overcoming Topology Agnosticism: Enhancing Skeleton-Based Action Recognition through Redefined Skeletal Topology Awareness
Yuxuan Zhou, Zhi-Qi Cheng, Jun-Yan He +3
Graph Convolutional Networks (GCNs) have long defined the state-of-the-art in skeleton-based action recognition, leveraging their ability to unravel the complex dynamics of human j…
Hypergraph Transformer for Skeleton-based Action Recognition
Yuxuan Zhou, Zhi-Qi Cheng, Chao Li +4
Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and thei…
Generative Action Description Prompts for Skeleton-based Action Recognition
Wangmeng Xiang, Chao Li, Yuxuan Zhou +2
Skeleton-based action recognition has recently received considerable attention. Current approaches to skeleton-based action recognition are typically formulated as one-hot classifi…
SP-ViT: Learning 2D Spatial Priors for Vision Transformers
Yuxuan Zhou, Wangmeng Xiang, Chao Li +5
Recently, transformers have shown great potential in image classification and established state-of-the-art results on the ImageNet benchmark. However, compared to CNNs, transformer…
Understanding Anomaly Detection with Deep Invertible Networks through Hierarchies of Distributions and Features
Robin Tibor Schirrmeister, Yuxuan Zhou, Tonio Ball +1
Deep generative networks trained via maximum likelihood on a natural image dataset like CIFAR10 often assign high likelihoods to images from datasets with different objects (e.g.,…