Zobrazeno 1 - 10
of 5 318
pro vyhledávání: '"HAN, Peng"'
Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movement in free space, or road trajectories, capturing movement in a road
Externí odkaz:
http://arxiv.org/abs/2411.14768
Due to the global trend towards urbanization, people increasingly move to and live in cities that then continue to grow. Traffic forecasting plays an important role in the intelligent transportation systems of cities as well as in spatio-temporal dat
Externí odkaz:
http://arxiv.org/abs/2410.19192
The inverse scattering transform for the defocusing-defocusing coupled Hirota equations is strictly discussed with non-zero boundary conditions at infinity including non-parallel boundary conditions, specifically referring to the asymptotic polarizat
Externí odkaz:
http://arxiv.org/abs/2410.15676
Living fish may suddenly encounter upstream obstacles, join the queue of the fish schooling, or detect upstream flow in advance, resulting in interactions with environmental vortices that can be abrupt or develop gradually from an initial state. The
Externí odkaz:
http://arxiv.org/abs/2409.17957
Autor:
Jiang, Xin, Li, Xiang, Ma, Wenjia, Fang, Xuezhi, Yao, Yiqun, Yu, Naitong, Meng, Xuying, Han, Peng, Li, Jing, Sun, Aixin, Wang, Yequan
Large language models (LLMs) represented by GPT family have achieved remarkable success. The characteristics of LLMs lie in their ability to accommodate a wide range of tasks through a generative approach. However, the flexibility of their output for
Externí odkaz:
http://arxiv.org/abs/2409.03346
Autor:
Yao, Yiqun, Ma, Wenjia, Fang, Xuezhi, Jiang, Xin, Li, Xiang, Meng, Xuying, Han, Peng, Li, Jing, Sun, Aixin, Wang, Yequan
Controlling the format of outputs generated by large language models (LLMs) is a critical functionality in various applications. Current methods typically employ constrained decoding with rule-based automata or fine-tuning with manually crafted forma
Externí odkaz:
http://arxiv.org/abs/2408.04392
Autor:
Gong, Chang, Yao, Di, Wang, Jin, Li, Wenbin, Fang, Lanting, Xie, Yongtao, Feng, Kaiyu, Han, Peng, Bi, Jingping
Root Cause Analysis (RCA) aims at identifying the underlying causes of system faults by uncovering and analyzing the causal structure from complex systems. It has been widely used in many application domains. Reliable diagnostic conclusions are of gr
Externí odkaz:
http://arxiv.org/abs/2407.05869
Autor:
Huang, Chengrui, Shi, Zhengliang, Wen, Yuntao, Chen, Xiuying, Han, Peng, Gao, Shen, Shang, Shuo
Tool learning methods have enhanced the ability of large language models (LLMs) to interact with real-world applications. Many existing works fine-tune LLMs or design prompts to enable LLMs to select appropriate tools and correctly invoke them to mee
Externí odkaz:
http://arxiv.org/abs/2407.03007
Bent functions are maximally nonlinear Boolean functions with an even number of variables, which include a subclass of functions, the so-called hyper-bent functions whose properties are stronger than bent functions and a complete classification of hy
Externí odkaz:
http://arxiv.org/abs/2407.01946
Autor:
Han, Peng
Learning to rank is utilized in many scenarios, such as disease-gene association, information retrieval and recommender system. Improving the prediction accuracy of the ranking model is the main target of existing works. Contextual information has a
Externí odkaz:
http://hdl.handle.net/10754/673398