6 papers
A Pragmatic VLA Foundation Model
Wei Wu, Fan Lu, Yunnan Wang +22
Offering great potential in robotic manipulation, a capable Vision-Language-Action (VLA) foundation model is expected to faithfully generalize across tasks and platforms while ensu…
MAR: Efficient Large Language Models via Module-aware Architecture Refinement
Junhong Cai, Guiqin Wang, Kejie Zhao +6
Large Language Models (LLMs) excel across diverse domains but suffer from high energy costs due to quadratic attention and dense Feed-Forward Network (FFN) operations. To address t…
Hebbian Learning with Global Direction
Wenjia Hua, Kejie Zhao, Luziwei Leng +3
Backpropagation algorithm has driven the remarkable success of deep neural networks, but its lack of biological plausibility and high computational costs have motivated the ongoing…
The Great March 100: 100 Detail-oriented Tasks for Evaluating Embodied AI Agents
Ziyu Wang, Chenyuan Liu, Yushun Xiang +16
Recently, with the rapid development of robot learning and imitation learning, numerous datasets and methods have emerged. However, these datasets and their task designs often lack…
Temporal-Guided Visual Foundation Models for Event-Based Vision
Ruihao Xia, Junhong Cai, Luziwei Leng +5
Event cameras offer unique advantages for vision tasks in challenging environments, yet processing asynchronous event streams remains an open challenge. While existing methods rely…
MetaBox-v2: A Unified Benchmark Platform for Meta-Black-Box Optimization
Zeyuan Ma, Yue-Jiao Gong, Hongshu Guo +11
Meta-Black-Box Optimization (MetaBBO) streamlines the automation of optimization algorithm design through meta-learning. It typically employs a bi-level structure: the meta-level p…