Publications (7)
Strengthened Symbol Binding Makes Large Language Models Reliable Multiple-Choice Selectors
Mengge Xue, Zhenyu Hu, Liqun Liu +5
Multiple-Choice Questions (MCQs) constitute a critical area of research in the study of Large Language Models (LLMs). Previous works have investigated the selection bias problem in…
Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report
Xufeng Zhao, Fuzhi Yang, Jianhui Chen +17
The motion controller is one of the most fundamental modules in embodied intelligence systems. Driven by large-scale human motion-capture data and the motion-tracking paradigm, hum…
ABot-N1: Toward a General Visual Language Navigation Foundation Model
Ruiyan Gong, Yingnan Guo, Junjun Hu +44
The paper presents ABot-N1, a visual‑language navigation foundation model that separates high‑level reasoning from low‑level control via a slow‑fast architecture and pixel‑based go…
ABot-N0: Technical Report on the VLA Foundation Model for Versatile Embodied Navigation
Zedong Chu, Shichao Xie, Xiaolong Wu +41
Embodied navigation has long been fragmented by task-specific architectures. We introduce ABot-N0, a unified Vision-Language-Action (VLA) foundation model that achieves a ``Grand U…
ABot-AgentOS: A General Robotic Agent OS with Lifelong Multi-modal Memory
Jiayi Tian, Shiao Liu, Yuting Xu +31
The paper introduces ABot-AgentOS, a general operating system layer for robotic agents that adds deliberative planning, multi‑modal memory, verification, and cloud‑edge collaborati…
Enhancing Reinforcement Learning with Label-Sensitive Reward for Natural Language Understanding
Kuo Liao, Shuang Li, Meng Zhao +5
Recent strides in large language models (LLMs) have yielded remarkable performance, leveraging reinforcement learning from human feedback (RLHF) to significantly enhance generation…