1 code implementation • EMNLP 2021 • Erguang Yang, Mingtong Liu, Deyi Xiong, Yujie Zhang, Yao Meng, Changjian Hu, Jinan Xu, Yufeng Chen
Particularly, we design a two-stage learning method to effectively train the model using non-parallel data.
no code implementations • Findings (NAACL) 2022 • Erguang Yang, Chenglin Bai, Deyi Xiong, Yujie Zhang, Yao Meng, Jinan Xu, Yufeng Chen
To model the alignment relation between words and nodes, we propose an attention regularization objective, which makes the decoder accurately select corresponding syntax nodes to guide the generation of words. Experiments show that SI-SCP achieves state-of-the-art performances in terms of semantic and syntactic quality on two popular benchmark datasets. Additionally, we propose a Syntactic Template Retriever (STR) to retrieve compatible syntactic structures.
no code implementations • 24 May 2023 • Mohsen Pourvali, Yao Meng, Chen Sheng, Yangzhou Du
Our obtained results show the significant effect of a taxonomy in increasing the performance of a learner in semisupervised multi-class classification and the considerable results obtained in a fully supervised fashion.
no code implementations • 19 May 2023 • Mingle Xu, Hyongsuk Kim, Jucheng Yang, Alvaro Fuentes, Yao Meng, Sook Yoon, Taehyun Kim, Dong Sun Park
We believe that our paper sheds light on the importance of embracing poor datasets, enhances the understanding of the associated challenges, and contributes to the ambitious objective of deploying deep learning in real-world applications.
no code implementations • COLING 2020 • Mingtong Liu, Erguang Yang, Deyi Xiong, Yujie Zhang, Yao Meng, Changjian Hu, Jinan Xu, Yufeng Chen
We propose a learning-exploring method to generate sentences as learning objectives from the learned data distribution, and employ reinforcement learning to combine these new learning objectives for model training.
no code implementations • COLING 2020 • Xu Cao, Deyi Xiong, Chongyang Shi, Chao Wang, Yao Meng, Changjian Hu
Joint intent detection and slot filling has recently achieved tremendous success in advancing the performance of utterance understanding.
no code implementations • WS 2020 • Hanchu Zhang, Leonhard Hennig, Christoph Alt, Changjian Hu, Yao Meng, Chao Wang
Named Entity Recognition (NER) in domains like e-commerce is an understudied problem due to the lack of annotated datasets.
no code implementations • 3 Apr 2020 • Ming Liang, Yao Meng, Jiyu Wang, David Lubkeman, Ning Lu
This paper presents a novel, automated, generative adversarial networks (GAN) based synthetic feeder generation mechanism, abbreviated as FeederGAN.
no code implementations • COLING 2016 • Hailong Cao, Tiejun Zhao, Shu Zhang, Yao Meng
We introduce a distribution based model to learn bilingual word embeddings from monolingual data.
no code implementations • 5 May 2015 • Shuangyong Song, Yao Meng, Zhongguang Zheng, Jun Sun
Our FRDC_QA team participated in the QA-Lab English subtask of the NTCIR-11.
no code implementations • 30 Apr 2015 • Shuangyong Song, Yao Meng
In this paper, we propose a Concept-level Emotion Cause Model (CECM), instead of the mere word-level models, to discover causes of microblogging users' diversified emotions on specific hot event.