no code implementations • EMNLP 2021 • Huimin Wang, Kam-Fai Wong
Most reinforcement learning methods for dialog policy learning train a centralized agent that selects a predefined joint action concatenating domain name, intent type, and slot name.
no code implementations • 28 Feb 2022 • Wai-Chung Kwan, Hongru Wang, Huimin Wang, Kam-Fai Wong
In this paper, we survey recent advances and challenges in dialogue policy from the prescriptive of RL.
no code implementations • 2 Nov 2021 • Hongru Wang, Huimin Wang, Zezhong Wang, Kam-Fai Wong
Reinforcement Learning (RL) has been witnessed its potential for training a dialogue policy agent towards maximizing the accumulated rewards given from users.
no code implementations • 14 Oct 2021 • Lingzhi Wang, Huang Hu, Lei Sha, Can Xu, Kam-Fai Wong, Daxin Jiang
In this paper, we present a pre-trained language model (PLM) based framework called RID for conversational recommender system (CRS).
no code implementations • 13 Oct 2021 • Hongru Wang, Zhijing Jin, Jiarun Cao, Gabriel Pui Cheong Fung, Kam-Fai Wong
However, previous works rarely investigate the effects of a different number of classes (i. e., $N$-way) and number of labeled data per class (i. e., $K$-shot) during training vs. testing.
no code implementations • 11 Sep 2021 • Zezhong Wang, Hongru Wang, Kwan Wai Chung, Jia Zhu, Gabriel Pui Cheong Fung, Kam-Fai Wong
To tackle this problem, we propose an effective similarity-based method to select data from the source domains.
no code implementations • 11 Sep 2021 • Hongru Wang, Mingyu Cui, Zimo Zhou, Gabriel Pui Cheong Fung, Kam-Fai Wong
A multi-turn dialogue always follows a specific topic thread, and topic shift at the discourse level occurs naturally as the conversation progresses, necessitating the model's ability to capture different topics and generate topic-aware responses.
1 code implementation • Findings (EMNLP) 2021 • Lingzhi Wang, Xingshan Zeng, Huang Hu, Kam-Fai Wong, Daxin Jiang
In recent years, world business in online discussions and opinion sharing on social media is booming.
1 code implementation • Findings (EMNLP) 2021 • Zhiming Mao, Xingshan Zeng, Kam-Fai Wong
In this work, we propose a news recommendation framework consisting of collaborative news encoding (CNE) and structural user encoding (SUE) to enhance news and user representation learning.
no code implementations • 26 Aug 2021 • Hongru Wang, Zezhong Wang, Gabriel Pui Cheong Fung, Kam-Fai Wong
Specifically, we propose a learn-from-memory mechanism that use explicit memory to keep track of the label representations of previously trained episodes and propose a contrastive learning method to compare the current label embedded in the few shot episode with the historic ones stored in the memory, and an adaption-from memory mechanism to determine the output label based on the contrast between the input labels embedded in the test episode and the label clusters in the memory.
1 code implementation • EMNLP 2020 • Lingzhi Wang, Jing Li, Xingshan Zeng, Haisong Zhang, Kam-Fai Wong
Quotations are crucial for successful explanations and persuasions in interpersonal communications.
1 code implementation • ACL 2021 • Lingzhi Wang, Xingshan Zeng, Kam-Fai Wong
To help individuals express themselves better, quotation recommendation is receiving growing attention.
no code implementations • 17 Nov 2020 • Hongru Wang, Min Li, Zimo Zhou, Gabriel Pui Cheong Fung, Kam-Fai Wong
In this paper, we publish a first Cantonese knowledge-driven Dialogue Dataset for REStaurant (KddRES) in Hong Kong, which grounds the information in multi-turn conversations to one specific restaurant.
no code implementations • ACL 2020 • Huimin Wang, Baolin Peng, Kam-Fai Wong
Training a task-oriented dialogue agent with reinforcement learning is prohibitively expensive since it requires a large volume of interactions with users.
no code implementations • ACL 2020 • Xingshan Zeng, Jing Li, Lu Wang, Zhiming Mao, Kam-Fai Wong
Trending topics in social media content evolve over time, and it is therefore crucial to understand social media users and their interpersonal communications in a dynamic manner.
no code implementations • SEMEVAL 2020 • Hongru Wang, Xiangru Tang, Sunny Lai, Kwong Sak Leung, Jia Zhu, Gabriel Pui Cheong Fung, Kam-Fai Wong
This paper describes our system submitted to task 4 of SemEval 2020: Commonsense Validation and Explanation (ComVE) which consists of three sub-tasks.
no code implementations • NAACL 2021 • Dingmin Wang, Chenghua Lin, Qi Liu, Kam-Fai Wong
We present a fast and scalable architecture called Explicit Modular Decomposition (EMD), in which we incorporate both classification-based and extraction-based methods and design four modules (for classification and sequence labelling) to jointly extract dialogue states.
no code implementations • IJCNLP 2019 • Xingshan Zeng, Jing Li, Lu Wang, Kam-Fai Wong
The prevalent use of social media leads to a vast amount of online conversations being produced on a daily basis.
no code implementations • IJCNLP 2019 • Ming Liao, Jing Li, Haisong Zhang, Lingzhi Wang, Xixin Wu, Kam-Fai Wong
Aspect words, indicating opinion targets, are essential in expressing and understanding human opinions.
no code implementations • ACL 2019 • Jing Ma, Wei Gao, Shafiq Joty, Kam-Fai Wong
Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications.
1 code implementation • ACL 2019 • Xingshan Zeng, Jing Li, Lu Wang, Kam-Fai Wong
We hypothesize that both the context of the ongoing conversations and the users' previous chatting history will affect their continued interests in future engagement.
no code implementations • CL 2018 • Jing Li, Yan Song, Zhongyu Wei, Kam-Fai Wong
To address this issue, we organize microblog messages as conversation trees based on their reposting and replying relations, and propose an unsupervised model that jointly learns word distributions to represent: (1) different roles of conversational discourse, and (2) various latent topics in reflecting content information.
no code implementations • 11 Sep 2018 • Jing Li, Yan Song, Zhongyu Wei, Kam-Fai Wong
To address this issue, we organize microblog messages as conversation trees based on their reposting and replying relations, and propose an unsupervised model that jointly learns word distributions to represent: 1) different roles of conversational discourse, 2) various latent topics in reflecting content information.
1 code implementation • ACL 2018 • Jing Ma, Wei Gao, Kam-Fai Wong
Automatic rumor detection is technically very challenging.
no code implementations • ACL 2018 • Zhongyu Wei, Qianlong Liu, Baolin Peng, Huaixiao Tou, Ting Chen, Xuanjing Huang, Kam-Fai Wong, Xiangying Dai
In this paper, we make a move to build a dialogue system for automatic diagnosis.
no code implementations • NAACL 2018 • Xingshan Zeng, Jing Li, Lu Wang, Nicholas Beauchamp, Sarah Shugars, Kam-Fai Wong
We propose a statistical model that jointly captures: (1) topics for representing user interests and conversation content, and (2) discourse modes for describing user replying behavior and conversation dynamics.
3 code implementations • ACL 2018 • Baolin Peng, Xiujun Li, Jianfeng Gao, Jingjing Liu, Kam-Fai Wong, Shang-Yu Su
During dialogue policy learning, the world model is constantly updated with real user experience to approach real user behavior, and in turn, the dialogue agent is optimized using both real experience and simulated experience.
no code implementations • IJCNLP 2017 • Liang-Chih Yu, Lung-Hao Lee, Jin Wang, Kam-Fai Wong
This paper presents the IJCNLP 2017 shared task on Dimensional Sentiment Analysis for Chinese Phrases (DSAP) which seeks to identify a real-value sentiment score of Chinese single words and multi-word phrases in the both valence and arousal dimensions.
no code implementations • WS 2017 • Gabriel Fung, Maxime Debosschere, Dingmin Wang, Bo Li, Jia Zhu, Kam-Fai Wong
This paper provides an overview along with our findings of the Chinese Spelling Check shared task at NLPTEA 2017.
no code implementations • 31 Oct 2017 • Baolin Peng, Xiujun Li, Jianfeng Gao, Jingjing Liu, Yun-Nung Chen, Kam-Fai Wong
This paper presents a new method --- adversarial advantage actor-critic (Adversarial A2C), which significantly improves the efficiency of dialogue policy learning in task-completion dialogue systems.
no code implementations • ACL 2017 • Jing Ma, Wei Gao, Kam-Fai Wong
How fake news goes viral via social media?
no code implementations • EMNLP 2017 • Baolin Peng, Xiujun Li, Lihong Li, Jianfeng Gao, Asli Celikyilmaz, Sungjin Lee, Kam-Fai Wong
Building a dialogue agent to fulfill complex tasks, such as travel planning, is challenging because the agent has to learn to collectively complete multiple subtasks.
reinforcement-learning
Task-Completion Dialogue Policy Learning
no code implementations • EACL 2017 • Baolin Peng, Michael Seltzer, Y.C. Ju, Geoffrey Zweig, Kam-Fai Wong
This is motivated by an actual system under development to assist in the order taking process.
no code implementations • COLING 2016 • Shichao Dong, Gabriel Pui Cheong Fung, Binyang Li, Baolin Peng, Ming Liao, Jia Zhu, Kam-Fai Wong
We present a system called ACE for Automatic Colloquialism and Errors detection for written Chinese.
no code implementations • 3 Jun 2016 • Kaisheng Yao, Baolin Peng, Geoffrey Zweig, Kam-Fai Wong
Experimental results indicate that the model outperforms previously proposed neural conversation architectures, and that using specificity in the objective function significantly improves performances for both generation and retrieval.
1 code implementation • 22 Aug 2015 • Baolin Peng, Zhengdong Lu, Hang Li, Kam-Fai Wong
For example, it improves the accuracy on Path Finding(10K) from 33. 4% [6] to over 98%.
no code implementations • LREC 2014 • Lanjun Zhou, Binyang Li, Zhongyu Wei, Kam-Fai Wong
The lack of open discourse corpus for Chinese brings limitations for many natural language processing tasks.
no code implementations • LREC 2012 • Yulan He, Hassan Saif, Zhongyu Wei, Kam-Fai Wong
There have been increasing interests in recent years in analyzing tweet messages relevant to political events so as to understand public opinions towards certain political issues.