113 citations · 689 across the 53 of their papers we have counts for
13 papers · 1 filter
Task-Oriented Dialog Systems that Consider Multiple Appropriate Responses under the Same Context
Yichi Zhang, Zhijian Ou, Zhou Yu
Conversations have an intrinsic one-to-many property, which means that multiple responses can be appropriate for the same dialog context. In task-oriented dialogs, this property le…
Importance-Aware Learning for Neural Headline Editing
Qingyang Wu, Lei Li, Hao Zhou +2
Many social media news writers are not professionally trained. Therefore, social media platforms have to hire professional editors to adjust amateur headlines to attract more reade…
Filling Conversation Ellipsis for Better Social Dialog Understanding
Xiyuan Zhang, Chengxi Li, Dian Yu +2
The phenomenon of ellipsis is prevalent in social conversations. Ellipsis increases the difficulty of a series of downstream language understanding tasks, such as dialog act predic…
End-to-End Trainable Non-Collaborative Dialog System
Yu Li, Kun Qian, Weiyan Shi +1
End-to-end task-oriented dialog models have achieved promising performance on collaborative tasks where users willingly coordinate with the system to complete a given task. While i…
Gunrock: A Social Bot for Complex and Engaging Long Conversations
Dian Yu, Michelle Cohn, Yi Mang Yang +12
Gunrock is the winner of the 2018 Amazon Alexa Prize, as evaluated by coherence and engagement from both real users and Amazon-selected expert conversationalists. We focus on under…
Abstractive Dialog Summarization with Semantic Scaffolds
Lin Yuan, Zhou Yu
The demand for abstractive dialog summary is growing in real-world applications. For example, customer service center or hospitals would like to summarize customer service interact…
Alternating Recurrent Dialog Model with Large-scale Pre-trained Language Models
Qingyang Wu, Yichi Zhang, Yu Li +1
Existing dialog system models require extensive human annotations and are difficult to generalize to different tasks. The recent success of large pre-trained language models such a…
Augmenting Non-Collaborative Dialog Systems with Explicit Semantic and Strategic Dialog History
Yiheng Zhou, Yulia Tsvetkov, Alan W Black +1
We study non-collaborative dialogs, where two agents have a conflict of interest but must strategically communicate to reach an agreement (e.g., negotiation). This setting poses ne…
Multimodal Unified Attention Networks for Vision-and-Language Interactions
Zhou Yu, Yuhao Cui, Jun Yu +2
Learning an effective attention mechanism for multimodal data is important in many vision-and-language tasks that require a synergic understanding of both the visual and textual co…
ActivityNet-QA: A Dataset for Understanding Complex Web Videos via Question Answering
Zhou Yu, Dejing Xu, Jun Yu +4
Recent developments in modeling language and vision have been successfully applied to image question answering. It is both crucial and natural to extend this research direction to…
Persuasion for Good: Towards a Personalized Persuasive Dialogue System for Social Good
Xuewei Wang, Weiyan Shi, Richard Kim +4
Developing intelligent persuasive conversational agents to change people's opinions and actions for social good is the frontier in advancing the ethical development of automated di…
Quantifying Intrinsic Uncertainty in Classification via Deep Dirichlet Mixture Networks
Qingyang Wu, He Li, Lexin Li +1
With the widespread success of deep neural networks in science and technology, it is becoming increasingly important to quantify the uncertainty of the predictions produced by deep…
Domain Adaptive Dialog Generation via Meta Learning
Kun Qian, Zhou Yu
Domain adaptation is an essential task in dialog system building because there are so many new dialog tasks created for different needs every day. Collecting and annotating trainin…