3 papers
cs.CL2026
Adam's Law: Textual Frequency Law on Large Language Models
Hongyuan Adam Lu, Z. L., Victor Wei +5
While textual frequency has been validated as relevant to human cognition in reading speed, its relatedness to Large Language Models (LLMs) is seldom studied. We propose a novel re…
cs.RO2025
Learning Efficient and Robust Language-conditioned Manipulation using Textual-Visual Relevancy and Equivariant Language Mapping
Mingxi Jia, Haojie Huang, Zhewen Zhang +7
Controlling robots through natural language is pivotal for enhancing human-robot collaboration and synthesizing complex robot behaviors. Recent works that are trained on large robo…
cs.RO2024
Equivariant Action Sampling for Reinforcement Learning and Planning
Linfeng Zhao, Owen Howell, Xupeng Zhu +4
Reinforcement learning (RL) algorithms for continuous control tasks require accurate sampling-based action selection. Many tasks, such as robotic manipulation, contain inherent pro…