6 papers
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,…
Decision SpikeFormer: Spike-Driven Transformer for Decision Making
Wei Huang, Qinying Gu, Nanyang Ye
Offline reinforcement learning (RL) enables policy training solely on pre-collected data, avoiding direct environment interaction - a crucial benefit for energy-constrained embodie…
OODD: Test-time Out-of-Distribution Detection with Dynamic Dictionary
Yifeng Yang, Lin Zhu, Zewen Sun +3
Out-of-distribution (OOD) detection remains challenging for deep learning models, particularly when test-time OOD samples differ significantly from training outliers. We propose OO…
Visual Position Prompt for MLLM based Visual Grounding
Wei Tang, Yanpeng Sun, Qinying Gu +1
Although Multimodal Large Language Models (MLLMs) excel at various image-related tasks, they encounter challenges in precisely aligning coordinates with spatial information within…
Enhancing Nursing and Elderly Care with Large Language Models: An AI-Driven Framework
Qiao Sun, Jiexin Xie, Nanyang Ye +2
This paper explores the application of large language models (LLMs) in nursing and elderly care, focusing on AI-driven patient monitoring and interaction. We introduce a novel Chin…
Synergistic Development of Perovskite Memristors and Algorithms for Robust Analog Computing
Nanyang Ye, Qiao Sun, Yifei Wang +10
Analog computing using non-volatile memristors has emerged as a promising solution for energy-efficient deep learning. New materials, like perovskites-based memristors are recently…