Embodied Artificial Intelligence (Embodied AI) is crucial for achieving Artificial General
Intelligence (AGI) and serves as a foundation for various applications that bridge cyberspace …

Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the
semantic web community's exploration into multi-modal dimensions unlocking new avenues …

Abstract 3D visual grounding aims to find the object within point clouds mentioned by free-
form natural language descriptions with rich semantic cues. However, existing methods …

Artificial intelligence (AI) is expected to be embodied in software agents, robots, and cyber-
physical systems that can understand the various contextual information of daily life in the …

The task of robot navigation and question answering, which is also known as Embodied
Question Answering (EQA), places its emphasis on empowering agents to actively explore …

We present and tackle the problem of Embodied Question Answering (EQA) with Situational
Queries (S-EQA) in a household environment. Unlike prior EQA work tackling simple queries …

There is no limit to how much a robot might explore and learn, but all of that knowledge
needs to be searchable and actionable. Within language research, retrieval augmented …

具身智能强调智能受脑, 身体与环境协同影响, 更侧重关注智能体与环境的“交互”. 因此,
在具身智能的研究中, 智能体的物理形态与感知, 学习, 控制的关系起到至关重要的作用. 当前 …

When adopting a deep learning model for embodied agents it is required that the model
structure be optimized for specific tasks and operational conditions. Such optimization can …

The task of relation extraction in natural language processing is to identify the relation
between two specified entities in a sentence. However, the existing model methods do not …