no code implementations • EMNLP 2020 • Yuntao Li, Bei Chen, Qian Liu, Yan Gao, Jian-Guang Lou, Yan Zhang, Dongmei Zhang
In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions.
no code implementations • 30 Apr 2024 • Lei Zhuang, Jingdong Zhao, Yuntao Li, Zichun Xu, Liangliang Zhao, Hong Liu
EISE and MPT are collaboratively trained, enabling EISE to autonomously learn and extract patterns from environmental data, thereby forming semantic representations that MPT could more effectively interpret and utilize for motion planning.
no code implementations • 12 Oct 2023 • Zirui Liang, Yuntao Li, Tianjin Huang, Akrati Saxena, Yulong Pei, Mykola Pechenizkiy
This leads to suboptimal performance of standard GNNs on imbalanced graphs.
1 code implementation • 14 Jun 2023 • Yuntao Li, Zhenpeng Su, Yutian Li, Hanchu Zhang, Sirui Wang, Wei Wu, Yan Zhang
Translating natural language queries into SQLs in a seq2seq manner has attracted much attention recently.
Ranked #8 on Text-To-SQL on spider
no code implementations • 16 Oct 2022 • Jian Song, Di Liang, Rumei Li, Yuntao Li, Sirui Wang, Minlong Peng, Wei Wu, Yongxin Yu
Transformer-based pre-trained models like BERT have achieved great progress on Semantic Sentence Matching.
no code implementations • COLING 2022 • Sirui Wang, Di Liang, Jian Song, Yuntao Li, Wei Wu
To alleviate this problem, we propose a novel Dual Attention Enhanced BERT (DABERT) to enhance the ability of BERT to capture fine-grained differences in sentence pairs.
no code implementations • 31 Aug 2022 • Sirui Wang, Kaiwen Wei, Hongzhi Zhang, Yuntao Li, Wei Wu
Inspired by the human learning process, in this paper, we introduce Imitation DEMOnstration Learning (Imitation-Demo) to strengthen demonstration learning via explicitly imitating human review behaviour, which includes: (1) contrastive learning mechanism to concentrate on the similar demonstrations.
1 code implementation • 16 Dec 2021 • Yuntao Li, Hanchu Zhang, Yutian Li, Sirui Wang, Wei Wu, Yan Zhang
Conversational text-to-SQL aims at converting multi-turn natural language queries into their corresponding SQL (Structured Query Language) representations.
Ranked #2 on Text-To-SQL on SParC
no code implementations • 19 Nov 2021 • Yuntao Li, Can Xu, Huang Hu, Lei Sha, Yan Zhang, Daxin Jiang
The sequence representation plays a key role in the learning of matching degree between the dialogue context and the response.
no code implementations • 13 Sep 2021 • Meiqi Chen, Yuan Zhang, Xiaoyu Kou, Yuntao Li, Yan Zhang
To tackle this issue, we propose r-GAT, a relational graph attention network to learn multi-channel entity representations.
1 code implementation • 9 Nov 2020 • Yuntao Li, Bei Chen, Qian Liu, Yan Gao, Jian-Guang Lou, Yan Zhang, Dongmei Zhang
In Natural Language Interfaces to Databases systems, the text-to-SQL technique allows users to query databases by using natural language questions.
no code implementations • 28 Oct 2020 • Xiaoyu Kou, Yankai Lin, Yuntao Li, Jiahao Xu, Peng Li, Jie zhou, Yan Zhang
Knowledge graph embedding (KGE), aiming to embed entities and relations into low-dimensional vectors, has attracted wide attention recently.
no code implementations • 11 Dec 2017 • Michael Bernico, Yuntao Li, Dingchao Zhang
In this paper, we investigate the impact of target dataset size and source/target domain similarity on model performance through a series of experiments.