2 code implementations • 30 May 2016 • Yang Liu, Chengjie Sun, Lei Lin, Xiaolong Wang
In our approach, the encoding of sentence is a two-stage process.
Ranked #73 on Natural Language Inference on SNLI
1 code implementation • 17 May 2016 • Zhen Xu, Bingquan Liu, Baoxun Wang, Chengjie Sun, Xiaolong Wang
Modeling human conversations is the essence for building satisfying chat-bots with multi-turn dialog ability.
no code implementations • SEMEVAL 2018 • Wenjie Liu, Chengjie Sun, Lei Lin, Bingquan Liu
Semantic Evaluation (SemEval) 2018 Task 12 {``}The Argument Reasoning Comprehension{''} committed to research natural language reasoning.
no code implementations • SEMEVAL 2017 • Wenjie Liu, Chengjie Sun, Lei Lin, Bingquan Liu
Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair.
no code implementations • EMNLP 2017 • Zhen Xu, Bingquan Liu, Baoxun Wang, Chengjie Sun, Xiaolong Wang, Zhuoran Wang, Chao Qi
This paper presents a Generative Adversarial Network (GAN) to model single-turn short-text conversations, which trains a sequence-to-sequence (Seq2Seq) network for response generation simultaneously with a discriminative classifier that measures the differences between human-produced responses and machine-generated ones.
no code implementations • 31 Dec 2020 • Shaobo Li, Xiaoguang Li, Lifeng Shang, Xin Jiang, Qun Liu, Chengjie Sun, Zhenzhou Ji, Bingquan Liu
In this paper, we propose a new retrieval target, hop, to collect the hidden reasoning evidence from Wikipedia for complex question answering.
Ranked #6 on Question Answering on HotpotQA
no code implementations • 7 Sep 2021 • Shaobo Li, Qun Liu, Xin Jiang, Yichun Yin, Chengjie Sun, Bingquan Liu, Zhenzhou Ji, Lifeng Shang
Human-designed rules are widely used to build industry applications.
no code implementations • SEMEVAL 2021 • Genyu Zhang, Yu Su, Changhong He, Lei Lin, Chengjie Sun, Lili Shan
This paper describes the winning system in the End-to-end Pipeline phase for the NLPContributionGraph task.
no code implementations • Findings (EMNLP) 2021 • Yunhe Xie, Kailai Yang, Chengjie Sun, Bingquan Liu, Zhenzhou Ji
However, these models neglect direct utterance-knowledge interaction.
Ranked #14 on Emotion Recognition in Conversation on DailyDialog
no code implementations • 25 Sep 2019 • Zhen Xu, Baoxun Wang, huan zhang, Kexin Qiu, Deyuan Zhang, Chengjie Sun
This paper presents a new methodology for modeling the local semantic distribution of responses to a given query in the human-conversation corpus, and on this basis, explores a specified adversarial learning mechanism for training Neural Response Generation (NRG) models to build conversational agents.
no code implementations • Findings (ACL) 2022 • Shaobo Li, Xiaoguang Li, Lifeng Shang, Zhenhua Dong, Chengjie Sun, Bingquan Liu, Zhenzhou Ji, Xin Jiang, Qun Liu
We check the words that have three typical associations with the missing words: knowledge-dependent, positionally close, and highly co-occurred.
no code implementations • SemEval (NAACL) 2022 • Zhongan Chen, Weiwei Chen, YunLong Sun, Hongqing Xu, Shuzhe Zhou, Bohan Chen, Chengjie Sun, Yuanchao Liu
This article introduces a system to solve the SemEval 2022 Task 8: Multilingual News Article Similarity.
no code implementations • 20 Oct 2022 • Shaobo Li, Xiaoguang Li, Lifeng Shang, Chengjie Sun, Bingquan Liu, Zhenzhou Ji, Xin Jiang, Qun Liu
Further experiments on question-answering datasets show that trying to learn a deterministic relationship with the proposed methods can also help other knowledge-intensive tasks.
no code implementations • 7 Oct 2023 • Weihe Zhai, Arkaitz Zubiaga, Bingquan Liu, Chengjie Sun, Yalong Zhao
While fusing language models and knowledge graphs has become common in commonsense question answering research, enabling faithful chain-of-thought explanations in these models remains an open problem.