5 papers
Clustering-Based Weight Orthogonalization for Stabilizing Deep Reinforcement Learning
Guoqing Ma, Yuhan Zhang, Yuming Dai +3
Reinforcement learning (RL) has made significant advancements, achieving superhuman performance in various tasks. However, RL agents often operate under the assumption of environme…
Agentic Lybic: Multi-Agent Execution System with Tiered Reasoning and Orchestration
Liangxuan Guo, Bin Zhu, Qingqian Tao +5
Autonomous agents for desktop automation struggle with complex multi-step tasks due to poor coordination and inadequate quality control. We introduce Agentic Lybic, a novel multi-a…
Visual Large Language Models Exhibit Human-Level Cognitive Flexibility in the Wisconsin Card Sorting Test
Guangfu Hao, Frederic Alexandre, Shan Yu
Cognitive flexibility has been extensively studied in human cognition but remains relatively unexplored in the context of Visual Large Language Models (VLLMs). This study assesses…
Flexible Tool Selection through Low-dimensional Attribute Alignment of Vision and Language
Guangfu Hao, Haojie Wen, Liangxuan Guo +3
Flexible tool selection reflects a complex cognitive ability that distinguishes humans from other species, yet computational models that capture this ability remain underdeveloped.…
Efficient Reinforcement Learning Through Adaptively Pretrained Visual Encoder
Yuhan Zhang, Guoqing Ma, Guangfu Hao +3
While Reinforcement Learning (RL) agents can successfully learn to handle complex tasks, effectively generalizing acquired skills to unfamiliar settings remains a challenge. One of…