3 citations · 5 across the 7 of their papers we have counts for
8 papers
LIBERO-Pro2.0: A Benchmark for Evaluating the Robustness of Embodied Foundation Models
Xueyang Zhou, Yangming Xu, Qianjiang Li +10
LIBERO has emerged as a widely adopted benchmark for evaluating robotic manipulation policies. However, strong performance on LIBERO does not necessarily indicate robust embodied c…
Bias Is a Subspace, Not a Coordinate: A Geometric Rethinking of Post-hoc Debiasing in Vision-Language Models
Dachuan Zhao, Weiyue Li, Zhenda Shen +4
Vision-Language Models (VLMs) have become indispensable for multimodal reasoning, yet their representations often encode and amplify demographic biases, resulting in biased associa…
LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
Xueyang Zhou, Yangming Xu, Guiyao Tie +5
LIBERO has emerged as a widely adopted benchmark for evaluating Vision-Language-Action (VLA) models; however, its current training and evaluation settings are problematic, often le…
Learning Primitive Embodied World Models: Towards Scalable Robotic Learning
Qiao Sun, Liujia Yang, Wei Tang +12
While video-generation-based embodied world models have gained increasing attention, their reliance on large-scale embodied interaction data remains a key bottleneck. The scarcity,…
Agentic Robot: A Brain-Inspired Framework for Vision-Language-Action Models in Embodied Agents
Zhejian Yang, Yongchao Chen, Xueyang Zhou +8
Long-horizon robotic manipulation poses significant challenges for autonomous systems, requiring extended reasoning, precise execution, and robust error recovery across complex seq…
CRAB: Cross-environment Agent Benchmark for Multimodal Language Model Agents
Tianqi Xu, Linyao Chen, Dai-Jie Wu +13
The development of autonomous agents increasingly relies on Multimodal Language Models (MLMs) to perform tasks described in natural language with GUI environments, such as websites…
Physics-Enhanced Multi-fidelity Learning for Optical Surface Imprint
Yongchao Chen
Human fingerprints serve as one unique and powerful characteristic for each person, from which policemen can recognize the identity. Similar to humans, many natural bodies and intr…
FedSSC: Shared Supervised-Contrastive Federated Learning
Sirui Hu, Ling Feng, Xiaohan Yang +1
Federated learning is widely used to perform decentralized training of a global model on multiple devices while preserving the data privacy of each device. However, it suffers from…