no code implementations • ACL (ECNLP) 2021 • Runze Liang, Ryuichi Takanobu, Feng-Lin Li, Ji Zhang, Haiqing Chen, Minlie Huang
To this end, we formalize the turn-level satisfaction estimation as a reinforcement learning problem, in which the model can be optimized with only session-level satisfaction labels.
no code implementations • 16 Aug 2022 • Ryuichi Takanobu, Hao Zhou, Yankai Lin, Peng Li, Jie zhou, Minlie Huang
Modeling these subtasks is consistent with the human agent's behavior patterns.
1 code implementation • 22 Jun 2021 • Silin Gao, Ryuichi Takanobu, Antoine Bosselut, Minlie Huang
To address this task, we propose a TOD system with semi-structured knowledge management, SeKnow, which extends the belief state to manage knowledge with both structured and unstructured contents.
1 code implementation • Findings (ACL) 2021 • Silin Gao, Ryuichi Takanobu, Wei Peng, Qun Liu, Minlie Huang
To address this task, we propose a TOD system with hybrid knowledge management, HyKnow.
1 code implementation • ACL 2021 • Yujia Qin, Yankai Lin, Ryuichi Takanobu, Zhiyuan Liu, Peng Li, Heng Ji, Minlie Huang, Maosong Sun, Jie zhou
Pre-trained Language Models (PLMs) have shown superior performance on various downstream Natural Language Processing (NLP) tasks.
2 code implementations • ACL 2021 • Jiexi Liu, Ryuichi Takanobu, Jiaxin Wen, Dazhen Wan, Hongguang Li, Weiran Nie, Cheng Li, Wei Peng, Minlie Huang
Most language understanding models in task-oriented dialog systems are trained on a small amount of annotated training data, and evaluated in a small set from the same distribution.
no code implementations • COLING 2020 • Peixin Huang, Xiang Zhao, Ryuichi Takanobu, Zhen Tan, Weidong Xiao
Most existing work on event extraction (EE) either follows a pipelined manner or uses a joint structure but is pipelined in essence.
1 code implementation • EMNLP 2021 • Wenchang Ma, Ryuichi Takanobu, Minlie Huang
Growing interests have been attracted in Conversational Recommender Systems (CRS), which explore user preference through conversational interactions in order to make appropriate recommendation.
Ranked #5 on Recommendation Systems on ReDial
3 code implementations • 12 Oct 2020 • Ting Han, Ximing Liu, Ryuichi Takanobu, Yixin Lian, Chongxuan Huang, Dazhen Wan, Wei Peng, Minlie Huang
In this paper, we introduce MultiWOZ 2. 3, in which we differentiate incorrect annotations in dialogue acts from dialogue states, identifying a lack of co-reference when publishing the updated dataset.
no code implementations • SIGDIAL (ACL) 2020 • Ryuichi Takanobu, Qi Zhu, Jinchao Li, Baolin Peng, Jianfeng Gao, Minlie Huang
There is a growing interest in developing goal-oriented dialog systems which serve users in accomplishing complex tasks through multi-turn conversations.
1 code implementation • ACL 2020 • Ryuichi Takanobu, Runze Liang, Minlie Huang
To avoid explicitly building a user simulator beforehand, we propose Multi-Agent Dialog Policy Learning, which regards both the system and the user as the dialog agents.
no code implementations • 17 Mar 2020 • Zheng Zhang, Ryuichi Takanobu, Qi Zhu, Minlie Huang, Xiaoyan Zhu
Due to the significance and value in human-computer interaction and natural language processing, task-oriented dialog systems are attracting more and more attention in both academic and industrial communities.
1 code implementation • ACL 2020 • Qi Zhu, Zheng Zhang, Yan Fang, Xiang Li, Ryuichi Takanobu, Jinchao Li, Baolin Peng, Jianfeng Gao, Xiaoyan Zhu, Minlie Huang
We present ConvLab-2, an open-source toolkit that enables researchers to build task-oriented dialogue systems with state-of-the-art models, perform an end-to-end evaluation, and diagnose the weakness of systems.
1 code implementation • IJCNLP 2019 • Ryuichi Takanobu, Hanlin Zhu, Minlie Huang
Many studies apply Reinforcement Learning to learn a dialog policy with the reward function which requires elaborate design and pre-specified user goals.
no code implementations • 25 Jun 2019 • Lizi Liao, Ryuichi Takanobu, Yunshan Ma, Xun Yang, Minlie Huang, Tat-Seng Chua
When traveling to a foreign country, we are often in dire need of an intelligent conversational agent to provide instant and informative responses to our various queries.
2 code implementations • ACL 2019 • Sungjin Lee, Qi Zhu, Ryuichi Takanobu, Xiang Li, Yaoqin Zhang, Zheng Zhang, Jinchao Li, Baolin Peng, Xiujun Li, Minlie Huang, Jianfeng Gao
We present ConvLab, an open-source multi-domain end-to-end dialog system platform, that enables researchers to quickly set up experiments with reusable components and compare a large set of different approaches, ranging from conventional pipeline systems to end-to-end neural models, in common environments.
no code implementations • 24 Feb 2019 • Ryuichi Takanobu, Tao Zhuang, Minlie Huang, Jun Feng, Haihong Tang, Bo Zheng
In this paper, we investigate the task of aggregating search results from heterogeneous sources in an E-commerce environment.
Hierarchical Reinforcement Learning reinforcement-learning +3
2 code implementations • 9 Nov 2018 • Ryuichi Takanobu, Tianyang Zhang, Jiexi Liu, Minlie Huang
The whole extraction process is decomposed into a hierarchy of two-level RL policies for relation detection and entity extraction respectively, so that it is more feasible and natural to deal with overlapping relations.
Ranked #2 on Relation Extraction on NYT24
Entity Extraction using GAN Hierarchical Reinforcement Learning +3