Zobrazeno 1 - 10
of 773
pro vyhledávání: '"BAI, Ting"'
As LLMs exhibit a high degree of human-like capability, increasing attention has been paid to role-playing research areas in which responses generated by LLMs are expected to mimic human replies. This has promoted the exploration of role-playing agen
Externí odkaz:
http://arxiv.org/abs/2410.23041
With the expansion of business scenarios, real recommender systems are facing challenges in dealing with the constantly emerging new tasks in multi-task learning frameworks. In this paper, we attempt to improve the generalization ability of multi-tas
Externí odkaz:
http://arxiv.org/abs/2408.17214
In this work, we address the problem of charging coordination between electric trucks and charging stations. The problem arises from the tension between the trucks' nontrivial charging times and the stations' limited charging facilities. Our goal is
Externí odkaz:
http://arxiv.org/abs/2407.10307
Autor:
Liu, Nian, Fan, Shen, Bai, Ting, Wang, Peng, Sun, Mingwei, Mo, Yanhu, Xu, Xiaoxiao, Liu, Hong, Shi, Chuan
Social relations have been widely incorporated into recommender systems to alleviate data sparsity problem. However, raw social relations don't always benefit recommendation due to their inferior quality and insufficient quantity, especially for inac
Externí odkaz:
http://arxiv.org/abs/2405.05288
Distributed Traffic Signal Control of Interconnected Intersections: A Two-Lane Traffic Network Model
Practical and accurate traffic models play an important role in capturing real traffic dynamics and then in achieving effective control performance. This paper studies traffic signal control in a traffic network with multiple interconnected intersect
Externí odkaz:
http://arxiv.org/abs/2401.11483
Electric trucks usually need to charge their batteries during long-range delivery missions, and the charging times are often nontrivial. As charging resources are limited, waiting times for some trucks can be prolonged at certain stations. To facilit
Externí odkaz:
http://arxiv.org/abs/2311.06874
Autor:
Liu, Jiawei, Yang, Cheng, Lu, Zhiyuan, Chen, Junze, Li, Yibo, Zhang, Mengmei, Bai, Ting, Fang, Yuan, Sun, Lichao, Yu, Philip S., Shi, Chuan
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains. Meanwhile, the field of graph machine learning is w
Externí odkaz:
http://arxiv.org/abs/2310.11829
Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by diffe
Externí odkaz:
http://arxiv.org/abs/2307.11867
Autor:
Ai, Qingyao, Bai, Ting, Cao, Zhao, Chang, Yi, Chen, Jiawei, Chen, Zhumin, Cheng, Zhiyong, Dong, Shoubin, Dou, Zhicheng, Feng, Fuli, Gao, Shen, Guo, Jiafeng, He, Xiangnan, Lan, Yanyan, Li, Chenliang, Liu, Yiqun, Lyu, Ziyu, Ma, Weizhi, Ma, Jun, Ren, Zhaochun, Ren, Pengjie, Wang, Zhiqiang, Wang, Mingwen, Wen, Ji-Rong, Wu, Le, Xin, Xin, Xu, Jun, Yin, Dawei, Zhang, Peng, Zhang, Fan, Zhang, Weinan, Zhang, Min, Zhu, Xiaofei
The research field of Information Retrieval (IR) has evolved significantly, expanding beyond traditional search to meet diverse user information needs. Recently, Large Language Models (LLMs) have demonstrated exceptional capabilities in text understa
Externí odkaz:
http://arxiv.org/abs/2307.09751
Learning effective high-order feature interactions is very crucial in the CTR prediction task. However, it is very time-consuming to calculate high-order feature interactions with massive features in online e-commerce platforms. Most existing methods
Externí odkaz:
http://arxiv.org/abs/2304.10711