1 code implementation • 20 May 2024 • Xiaobo Liang, Haoke Zhang, Helan Hu, Juntao Li, Jun Xu, Min Zhang
The rapid advancement of large language models has given rise to a plethora of applications across a myriad of real-world tasks, mainly centered on aligning with human intent.
2 code implementations • 13 Dec 2021 • Chong Liu, Xiaoyang Liu, Rongqin Zheng, Lixin Zhang, Xiaobo Liang, Juntao Li, Lijun Wu, Min Zhang, Leyu Lin
State-of-the-art sequential recommendation models proposed very recently combine contrastive learning techniques for obtaining high-quality user representations.
no code implementations • 29 Sep 2021 • Xiaobo Liang, Runze Mao, Lijun Wu, Juntao Li, Weiqing Liu, Qing Li, Min Zhang
The common approach of consistency training is performed on the data-level, which typically utilizes the data augmentation strategy (or adversarial training) to make the predictions from the augmented input and the original input to be consistent, so that the model is more robust and attains better generalization ability.
no code implementations • 29 Sep 2021 • Yue Wang, Lijun Wu, Xiaobo Liang, Juntao Li, Min Zhang
Starting from the resurgence of deep learning, language models (LMs) have never been so popular.
9 code implementations • NeurIPS 2021 • Xiaobo Liang, Lijun Wu, Juntao Li, Yue Wang, Qi Meng, Tao Qin, Wei Chen, Min Zhang, Tie-Yan Liu
Dropout is a powerful and widely used technique to regularize the training of deep neural networks.
Ranked #4 on Machine Translation on WMT2014 English-French
1 code implementation • ACL 2019 • Chen Jia, Xiaobo Liang, Yue Zhang
Due to limitation of labeled resources, cross-domain named entity recognition (NER) has been a challenging task.
no code implementations • 17 Dec 2018 • Feiliang Ren, Yining Hou, Yan Li, Linfeng Pan, Yi Zhang, Xiaobo Liang, Yongkang Liu, Yu Guo, Rongsheng Zhao, Ruicheng Ming, Huiming Wu
In this work, we introduce TechKG, a large scale Chinese knowledge graph that is technology-oriented.
no code implementations • COLING 2018 • Feiliang Ren, Di Zhou, Zhihui Liu, Yongcheng Li, Rongsheng Zhao, Yongkang Liu, Xiaobo Liang
State-of-the-art methods usually concentrate on building deep neural networks based classification models on the training data in which the relations of the labeled entity pairs are given.