1 code implementation • NAACL 2022 • Yongwei Zhou, Junwei Bao, Chaoqun Duan, Haipeng Sun, Jiahui Liang, Yifan Wang, Jing Zhao, Youzheng Wu, Xiaodong He, Tiejun Zhao
To inherit the advantages of these two types of methods, we propose OPERA, an operation-pivoted discrete reasoning framework, where lightweight symbolic operations (compared with logical forms) as neural modules are utilized to facilitate the reasoning ability and interpretability.
no code implementations • 22 Aug 2023 • Yingyao Wang, Yongwei Zhou, Chaoqun Duan, Junwei Bao, Tiejun Zhao
To alleviate these challenges, we propose a self-iterative framework for multi-hop program generation (HopPG) over heterogeneous knowledge, which leverages the previous execution results to retrieve supporting facts and generate subsequent programs hop by hop.
1 code implementation • 19 Oct 2022 • Yingyao Wang, Junwei Bao, Chaoqun Duan, Youzheng Wu, Xiaodong He, Tiejun Zhao
To preserve the advantage and eliminate the disadvantage of different granularity evidence, we propose MuGER$^2$, a Multi-Granularity Evidence Retrieval and Reasoning approach.
1 code implementation • 15 Oct 2022 • Yongwei Zhou, Junwei Bao, Chaoqun Duan, Youzheng Wu, Xiaodong He, Tiejun Zhao
Question answering requiring discrete reasoning, e. g., arithmetic computing, comparison, and counting, over knowledge is a challenging task.
1 code implementation • NAACL 2022 • Yifan Wang, Jing Zhao, Junwei Bao, Chaoqun Duan, Youzheng Wu, Xiaodong He
Dialogue state tracking (DST) aims to predict the current dialogue state given the dialogue history.
no code implementations • 29 Apr 2022 • Yongwei Zhou, Junwei Bao, Chaoqun Duan, Haipeng Sun, Jiahui Liang, Yifan Wang, Jing Zhao, Youzheng Wu, Xiaodong He, Tiejun Zhao
To inherit the advantages of these two types of methods, we propose OPERA, an operation-pivoted discrete reasoning framework, where lightweight symbolic operations (compared with logical forms) as neural modules are utilized to facilitate the reasoning ability and interpretability.
no code implementations • 28 Feb 2020 • Chaoqun Duan, Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita, Conghui Zhu, Tiejun Zhao
Existing neural machine translation (NMT) systems utilize sequence-to-sequence neural networks to generate target translation word by word, and then make the generated word at each time-step and the counterpart in the references as consistent as possible.
no code implementations • 7 Feb 2020 • Chaoqun Duan, Lei Cui, Shuming Ma, Furu Wei, Conghui Zhu, Tiejun Zhao
In this work, we aim to improve the relevance between live comments and videos by modeling the cross-modal interactions among different modalities.