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检索条件"机构=Knowledge and Data Engineering"
2104 条 记 录,以下是11-20 订阅
排序:
Dual-Aspect Noise-Based Regularization for Multi-Modal Relation Extraction in Media Posts
IEEE Transactions on Audio, Speech and Language Processing
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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 1324-1336页
作者: Kai Sun Bin Shi Samuel Mensah Wenjian Liu Bo Dong School of Computer Science and Technology and Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Xi'an China School of Computer Science and Technology The University of Sheffield Sheffield U.K. Faculty of Data Science City University of Macau Macau China School of Continuing Education and Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Xi'an China
Multi-Modal Relation Extraction (MMRE) plays a key role in various multimedia applications including, recommendation and information retrieval systems. MMRE aims to extract the semantic relation between entities by le... 详细信息
来源: 评论
CoT-based Synthesizer: Enhancing LLM Performance through Answer Synthesis
arXiv
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arXiv 2025年
作者: Zhang, Bohan Zhang, Xiaokang Zhang, Jing Yu, Jifan Luo, Sijia Tang, Jie School of Information Renmin University of China China Tsinghua University China Key Laboratory of Data Engineering and Knowledge Engineering Beijing China
Current inference scaling methods, such as Self-consistency and Best-of-N, have proven effective in improving the accuracy of LLMs on complex reasoning tasks. However, these methods rely heavily on the quality of cand... 详细信息
来源: 评论
Dynamic Scaling of Unit Tests for Code Reward Modeling
arXiv
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arXiv 2025年
作者: Ma, Zeyao Zhang, Xiaokang Zhang, Jing Yu, Jifan Luo, Sijia Tang, Jie School of Information Renmin University of China China Tsinghua University China Key Laboratory of Data Engineering and Knowledge Engineering Beijing China
Current large language models (LLMs) often struggle to produce accurate solutions on the first attempt for code generation. Prior research tackles this challenge by generating multiple candidate solutions and validati...
来源: 评论
Fair Personalized Learner Modeling Without Sensitive Attributes  25
Fair Personalized Learner Modeling Without Sensitive Attribu...
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Proceedings of the ACM on Web Conference 2025
作者: Hefei Xu Min Hou Le Wu Fei Liu Yonghui Yang Haoyue Bai Richang Hong Meng Wang Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei Anhui China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Hefei Anhui China and Institute of Dataspace Hefei Comprehensive National Science Center Hefei Hefei Anhui China
Personalized learner modeling uses learners' historical behavior data to diagnose their cognitive abilities, a process known as Cognitive Diagnosis (CD). This is essential for web-based learning services such as l... 详细信息
来源: 评论
A Part-of-Speech Tagging Model Employing Word Clustering and Syntactic Parsing
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Chinese Journal of Electronics 2025年 第1期23卷 109-114页
作者: Lichi Yuan School of Information Technology Jiangxi University of Finance and Economics Nanchang China Jiangxi Key Laboratory of Data and Knowledge Engineering Jiangxi University of Finance and Economics Nanchang China
Part-Of-Speech tagging is a basic task in the field of natural language processing. This paper builds a POS tagger based on improved Hidden Markov model, by employing word clustering and syntactic parsing model. First...
来源: 评论
How to Mitigate Information Loss in knowledge Graphs for GraphRAG: Leveraging Triple Context Restoration and Query-Driven Feedback
arXiv
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arXiv 2025年
作者: Huang, Manzong Bu, Chenyang He, Yi Wu, Xindong Key Laboratory of Knowledge Engineering with Big Data [Hefei University of Technology Ministry of Education China School of Data Science William & Mary WilliamsburgVA United States
knowledge Graph (KG)-augmented Large Language Models (LLMs) have recently propelled significant advances in complex reasoning tasks, thanks to their broad domain knowledge and contextual awareness. Unfortunately, curr... 详细信息
来源: 评论
KAN v.s. MLP for Offline Reinforcement Learning
KAN v.s. MLP for Offline Reinforcement Learning
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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025
作者: Guo, Haihong Li, Fengxin Li, Jiao Liu, Hongyan School of Information Renmin University of China China Institute of Medical Information Medical Library Chinese Academy of Medical Sciences Peking Union Medical College China Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education China School of Economics and Management Tsinghua University China
Kolmogorov-Arnold Networks (KAN) is an emerging neural network architecture in machine learning. It has greatly interested the research community about whether KAN can be a promising alternative to the commonly used M... 详细信息
来源: 评论
A Query Optimization Method Utilizing Large Language Models
arXiv
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arXiv 2025年
作者: Yao, Zhiming Li, Haoyang Zhang, Jing Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Engineering Research Center of Database and Business Intelligence MOE China
Query optimization is a critical task in database systems, focused on determining the most efficient way to execute a query from an enormous set of possible strategies. Traditional approaches rely on heuristic search ... 详细信息
来源: 评论
LLMIdxAdvis: Resource-Efficient Index Advisor Utilizing Large Language Model
arXiv
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arXiv 2025年
作者: Zhao, Xinxin Li, Haoyang Zhang, Jing Huang, Xinmei Zhang, Tieying Chen, Jianjun Shi, Rui Li, Cuiping Chen, Hong School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Engineering Research Center of Database and Business Intelligence MOE China ByteDance China
Index recommendation is essential for improving query performance in database management systems (DBMSs) through creating an optimal set of indexes under specific constraints. Traditional methods, such as heuristic an... 详细信息
来源: 评论
OmniSQL: Synthesizing High-quality Text-to-SQL data at Scale
arXiv
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arXiv 2025年
作者: Li, Haoyang Wu, Shang Zhang, Xiaokang Huang, Xinmei Zhang, Jing Jiang, Fuxin Wang, Shuai Zhang, Tieying Chen, Jianjun Shi, Rui Chen, Hong Li, Cuiping Engineering Research Center of Database and Business Intelligence MOE China School of Information Renmin University of China Beijing China Key Laboratory of Data Engineering and Knowledge Engineering MOE China ByteDance Inc China
Text-to-SQL, the task of translating natural language questions into SQL queries, plays a crucial role in enabling non-experts to interact with databases. While recent advancements in large language models (LLMs) have... 详细信息
来源: 评论