113 citations · 689 across the 53 of their papers we have counts for
54 papers
Fantastic Questions and Where to Find Them: FairytaleQA -- An Authentic Dataset for Narrative Comprehension
Ying Xu, Dakuo Wang, Mo Yu +15
Question answering (QA) is a fundamental means to facilitate assessment and training of narrative comprehension skills for both machines and young children, yet there is scarcity o…
IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
Pan Lu, Liang Qiu, Jiaqi Chen +6
Current visual question answering (VQA) tasks mainly consider answering human-annotated questions for natural images. However, aside from natural images, abstract diagrams with sem…
Zero-Shot Dialogue State Tracking via Cross-Task Transfer
Zhaojiang Lin, Bing Liu, Andrea Madotto +8
Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data. In…
GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation
Derek Chen, Zhou Yu
Practical dialogue systems require robust methods of detecting out-of-scope (OOS) utterances to avoid conversational breakdowns and related failure modes. Directly training a model…
ROSITA: Enhancing Vision-and-Language Semantic Alignments via Cross- and Intra-modal Knowledge Integration
Yuhao Cui, Zhou Yu, Chunqi Wang +4
Vision-and-language pretraining (VLP) aims to learn generic multimodal representations from massive image-text pairs. While various successful attempts have been proposed, learning…
Selective Differential Privacy for Language Modeling
Weiyan Shi, Aiqi Cui, Evan Li +2
With the increasing applications of language models, it has become crucial to protect these models from leaking private information. Previous work has attempted to tackle this chal…
Evaluation of In-Person Counseling Strategies To Develop Physical Activity Chatbot for Women
Kai-Hui Liang, Patrick Lange, Yoo Jung Oh +3
Artificial intelligence chatbots are the vanguard in technology-based intervention to change people's behavior. To develop intervention chatbots, the first step is to understand na…
The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity
David Gros, Yu Li, Zhou Yu
Humans are increasingly interacting with machines through language, sometimes in contexts where the user may not know they are talking to a machine (like over the phone or a text c…
Towards Emotional Support Dialog Systems
Siyang Liu, Chujie Zheng, Orianna Demasi +5
Emotional support is a crucial ability for many conversation scenarios, including social interactions, mental health support, and customer service chats. Following reasonable proce…
HERALD: An Annotation Efficient Method to Detect User Disengagement in Social Conversations
Weixin Liang, Kai-Hui Liang, Zhou Yu
Open-domain dialog systems have a user-centric goal: to provide humans with an engaging conversation experience. User engagement is one of the most important metrics for evaluating…
SocAoG: Incremental Graph Parsing for Social Relation Inference in Dialogues
Liang Qiu, Yuan Liang, Yizhou Zhao +5
Inferring social relations from dialogues is vital for building emotionally intelligent robots to interpret human language better and act accordingly. We model the social network a…
Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon +7
Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper,…
LEGOEval: An Open-Source Toolkit for Dialogue System Evaluation via Crowdsourcing
Yu Li, Josh Arnold, Feifan Yan +2
We present LEGOEval, an open-source toolkit that enables researchers to easily evaluate dialogue systems in a few lines of code using the online crowdsource platform, Amazon Mechan…
Annotation Inconsistency and Entity Bias in MultiWOZ
Kun Qian, Ahmad Beirami, Zhouhan Lin +4
MultiWOZ is one of the most popular multi-domain task-oriented dialog datasets, containing 10K+ annotated dialogs covering eight domains. It has been widely accepted as a benchmark…
DEUX: An Attribute-Guided Framework for Sociable Recommendation Dialog Systems
Yu Li, Shirley Anugrah Hayati, Weiyan Shi +1
It is important for sociable recommendation dialog systems to perform as both on-task content and social content to engage users and gain their favor. In addition to understand the…
A Student-Teacher Architecture for Dialog Domain Adaptation under the Meta-Learning Setting
Kun Qian, Wei Wei, Zhou Yu
Numerous new dialog domains are being created every day while collecting data for these domains is extremely costly since it involves human interactions. Therefore, it is essential…
Revealing Persona Biases in Dialogue Systems
Emily Sheng, Josh Arnold, Zhou Yu +2
Dialogue systems in the form of chatbots and personal assistants are being increasingly integrated into people's lives. Modern dialogue systems may consider adopting anthropomorphi…
Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems
Derek Chen, Howard Chen, Yi Yang +2
Existing goal-oriented dialogue datasets focus mainly on identifying slots and values. However, customer support interactions in reality often involve agents following multi-step p…
Attribute Alignment: Controlling Text Generation from Pre-trained Language Models
Dian Yu, Zhou Yu, Kenji Sagae
Large language models benefit from training with a large amount of unlabeled text, which gives them increasingly fluent and diverse generation capabilities. However, using these mo…
ChainCQG: Flow-Aware Conversational Question Generation
Jing Gu, Mostafa Mirshekari, Zhou Yu +1
Conversational systems enable numerous valuable applications, and question-answering is an important component underlying many of these. However, conversational question-answering…
Continual Learning in Task-Oriented Dialogue Systems
Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou +6
Continual learning in task-oriented dialogue systems can allow us to add new domains and functionalities through time without incurring the high cost of a whole system retraining.…
Refine and Imitate: Reducing Repetition and Inconsistency in Persuasion Dialogues via Reinforcement Learning and Human Demonstration
Weiyan Shi, Yu Li, Saurav Sahay +1
Persuasion dialogue systems reflect the machine's ability to make strategic moves beyond verbal communication, and therefore differentiate themselves from task-oriented or open-dom…
Gunrock 2.0: A User Adaptive Social Conversational System
Kaihui Liang, Austin Chau, Yu Li +8
Gunrock 2.0 is built on top of Gunrock with an emphasis on user adaptation. Gunrock 2.0 combines various neural natural language understanding modules, including named entity detec…
Spoken Language Interaction with Robots: Research Issues and Recommendations, Report from the NSF Future Directions Workshop
Matthew Marge, Carol Espy-Wilson, Nigel Ward
With robotics rapidly advancing, more effective human-robot interaction is increasingly needed to realize the full potential of robots for society. While spoken language must be pa…