Zobrazeno 1 - 10
of 110
pro vyhledávání: '"Du, Lun"'
Autor:
Chen, Yuyan, Fu, Qiang, Fan, Ge, Du, Lun, Lou, Jian-Guang, Han, Shi, Zhang, Dongmei, Li, Zhixu, Xiao, Yanghua
Recent years, Pre-trained Language models (PLMs) have swept into various fields of artificial intelligence and achieved great success. However, most PLMs, such as T5 and GPT3, have a huge amount of parameters, fine-tuning them is often expensive and
Externí odkaz:
http://arxiv.org/abs/2407.11033
Foundation models, such as Large language Models (LLMs), have attracted significant amount of interest due to their large number of applications. However, when handling tasks involving repetitive sub-tasks and/or deceptive contents, such as arithmeti
Externí odkaz:
http://arxiv.org/abs/2402.05359
Autor:
He, Xinyi, Zhou, Mengyu, Xu, Xinrun, Ma, Xiaojun, Ding, Rui, Du, Lun, Gao, Yan, Jia, Ran, Chen, Xu, Han, Shi, Yuan, Zejian, Zhang, Dongmei
Tabular data analysis is crucial in various fields, and large language models show promise in this area. However, current research mostly focuses on rudimentary tasks like Text2SQL and TableQA, neglecting advanced analysis like forecasting and chart
Externí odkaz:
http://arxiv.org/abs/2312.13671
Autor:
Chen, Hao, Du, Lun, Lu, Yuxuan, Fu, Qiang, Chen, Xu, Han, Shi, Kang, Yanbin, Lu, Guangming, Li, Zi
Online recruitment platforms typically employ Person-Job Fit models in the core service that automatically match suitable job seekers with appropriate job positions. While existing works leverage historical or contextual information, they often disre
Externí odkaz:
http://arxiv.org/abs/2401.00010
Table reasoning tasks have shown remarkable progress with the development of large language models (LLMs), which involve interpreting and drawing conclusions from tabular data based on natural language (NL) questions. Existing solutions mainly tested
Externí odkaz:
http://arxiv.org/abs/2312.09039
Autor:
Liao, Jiayi, Chen, Xu, Fu, Qiang, Du, Lun, He, Xiangnan, Wang, Xiang, Han, Shi, Zhang, Dongmei
Recent years have witnessed the substantial progress of large-scale models across various domains, such as natural language processing and computer vision, facilitating the expression of concrete concepts. Unlike concrete concepts that are usually di
Externí odkaz:
http://arxiv.org/abs/2309.14623
Autor:
Shi, Ensheng, Zhang, Fengji, Wang, Yanlin, Chen, Bei, Du, Lun, Zhang, Hongyu, Han, Shi, Zhang, Dongmei, Sun, Hongbin
Software development plays a crucial role in driving innovation and efficiency across modern societies. To meet the demands of this dynamic field, there is a growing need for an effective software development assistant. However, existing large langua
Externí odkaz:
http://arxiv.org/abs/2308.13416
Collaborative filtering (CF) is an important research direction in recommender systems that aims to make recommendations given the information on user-item interactions. Graph CF has attracted more and more attention in recent years due to its effect
Externí odkaz:
http://arxiv.org/abs/2306.03624
Autor:
Yue, Chongjian, Xu, Xinrun, Ma, Xiaojun, Du, Lun, Liu, Hengyu, Ding, Zhiming, Jiang, Yanbing, Han, Shi, Zhang, Dongmei
Large Language Models (LLMs) demonstrate exceptional performance in textual understanding and tabular reasoning tasks. However, their ability to comprehend and analyze hybrid text, containing textual and tabular data, remains underexplored. In this r
Externí odkaz:
http://arxiv.org/abs/2305.16344
Large language models~(LLM) like ChatGPT have become indispensable to artificial general intelligence~(AGI), demonstrating excellent performance in various natural language processing tasks. In the real world, graph data is ubiquitous and an essentia
Externí odkaz:
http://arxiv.org/abs/2305.15066