Zobrazeno 1 - 10
of 212
pro vyhledávání: '"Shi, Haochen"'
Tactile feedback is critical for understanding the dynamics of both rigid and deformable objects in many manipulation tasks, such as non-prehensile manipulation and dense packing. We introduce an approach that combines visual and tactile sensing for
Externí odkaz:
http://arxiv.org/abs/2407.01418
Autor:
Wang, Weiqi, Fang, Tianqing, Shi, Haochen, Xu, Baixuan, Ding, Wenxuan, Zhang, Liyu, Fan, Wei, Bai, Jiaxin, Li, Haoran, Liu, Xin, Song, Yangqiu
Entity- and event-level conceptualization, as fundamental elements of human cognition, plays a pivotal role in generalizable reasoning. This process involves abstracting specific instances into higher-level concepts and forming abstract knowledge tha
Externí odkaz:
http://arxiv.org/abs/2406.10885
Autor:
Xu, Baixuan, Wang, Weiqi, Shi, Haochen, Ding, Wenxuan, Jing, Huihao, Fang, Tianqing, Bai, Jiaxin, Chen, Long, Song, Yangqiu
Improving user experience and providing personalized search results in E-commerce platforms heavily rely on understanding purchase intention. However, existing methods for acquiring large-scale intentions bank on distilling large language models with
Externí odkaz:
http://arxiv.org/abs/2406.10701
Imitation learning from human hand motion data presents a promising avenue for imbuing robots with human-like dexterity in real-world manipulation tasks. Despite this potential, substantial challenges persist, particularly with the portability of exi
Externí odkaz:
http://arxiv.org/abs/2403.07788
Embodied Instruction Following (EIF) is a crucial task in embodied learning, requiring agents to interact with their environment through egocentric observations to fulfill natural language instructions. Recent advancements have seen a surge in employ
Externí odkaz:
http://arxiv.org/abs/2403.03017
Autor:
Lu, Feihong, Wang, Weiqi, Luo, Yangyifei, Zhu, Ziqin, Sun, Qingyun, Xu, Baixuan, Shi, Haochen, Gao, Shiqi, Li, Qian, Song, Yangqiu, Li, Jianxin
Social media has become a ubiquitous tool for connecting with others, staying updated with news, expressing opinions, and finding entertainment. However, understanding the intention behind social media posts remains challenging due to the implicitnes
Externí odkaz:
http://arxiv.org/abs/2402.18169
Autor:
Wang, Weiqi, Fang, Tianqing, Li, Chunyang, Shi, Haochen, Ding, Wenxuan, Xu, Baixuan, Wang, Zhaowei, Bai, Jiaxin, Liu, Xin, Cheng, Jiayang, Chan, Chunkit, Song, Yangqiu
The sequential process of conceptualization and instantiation is essential to generalizable commonsense reasoning as it allows the application of existing knowledge to unfamiliar scenarios. However, existing works tend to undervalue the step of insta
Externí odkaz:
http://arxiv.org/abs/2401.07286
In this study, we explore the application of Large Language Models (LLMs) in \textit{Jubensha}, a Chinese detective role-playing game and a novel area in Artificial Intelligence (AI) driven gaming. We introduce the first dataset specifically for Jube
Externí odkaz:
http://arxiv.org/abs/2312.00746
Autor:
Wang, Zhaowei, Shi, Haochen, Wang, Weiqi, Fang, Tianqing, Zhang, Hongming, Choi, Sehyun, Liu, Xin, Song, Yangqiu
Cognitive research indicates that abstraction ability is essential in human intelligence, which remains under-explored in language models. In this paper, we present AbsPyramid, a unified entailment graph of 221K textual descriptions of abstraction kn
Externí odkaz:
http://arxiv.org/abs/2311.09174
Autor:
Shi, Haochen, Wang, Weiqi, Fang, Tianqing, Xu, Baixuan, Ding, Wenxuan, Liu, Xin, Song, Yangqiu
Zero-shot commonsense Question-Answering (QA) requires models to reason about general situations beyond specific benchmarks. State-of-the-art approaches fine-tune language models on QA pairs constructed from CommonSense Knowledge Bases (CSKBs) to equ
Externí odkaz:
http://arxiv.org/abs/2310.11303