45 citations · 58 across the 10 of their papers we have counts for
10 papers
Deep Prompt Multi-task Network for Abuse Language Detection
Jian Zhu, Yuping Ruan, Jingfei Chang +4
The detection of abusive language remains a long-standing challenge with the extensive use of social networks. The detection task of abusive language suffers from limited accuracy.…
Evaluating Robustness of Dialogue Summarization Models in the Presence of Naturally Occurring Variations
Ankita Gupta, Chulaka Gunasekara, Hui Wan +3
Dialogue summarization task involves summarizing long conversations while preserving the most salient information. Real-life dialogues often involve naturally occurring variations…
How Can Context Help? Exploring Joint Retrieval of Passage and Personalized Context
Hui Wan, Hongkang Li, Songtao Lu +2
The integration of external personalized context information into document-grounded conversational systems has significant potential business value, but has not been well-studied.…
Semi-Structured Object Sequence Encoders
Rudra Murthy, Riyaz Bhat, Chulaka Gunasekara +5
In this paper we explore the task of modeling semi-structured object sequences; in particular, we focus our attention on the problem of developing a structure-aware input represent…
Fast and Light-Weight Answer Text Retrieval in Dialogue Systems
Hui Wan, Siva Sankalp Patel, J. William Murdock +2
Dialogue systems can benefit from being able to search through a corpus of text to find information relevant to user requests, especially when encountering a request for which no m…
Learning as Conversation: Dialogue Systems Reinforced for Information Acquisition
Pengshan Cai, Hui Wan, Fei Liu +3
We propose novel AI-empowered chat bots for learning as conversation where a user does not read a passage but gains information and knowledge through conversation with a teacher bo…
MultiDoc2Dial: Modeling Dialogues Grounded in Multiple Documents
Song Feng, Siva Sankalp Patel, Hui Wan +1
We propose MultiDoc2Dial, a new task and dataset on modeling goal-oriented dialogues grounded in multiple documents. Most previous works treat document-grounded dialogue modeling a…
Explaining Neural Network Predictions on Sentence Pairs via Learning Word-Group Masks
Hanjie Chen, Song Feng, Jatin Ganhotra +4
Explaining neural network models is important for increasing their trustworthiness in real-world applications. Most existing methods generate post-hoc explanations for neural netwo…
doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset
Song Feng, Hui Wan, Chulaka Gunasekara +3
We introduce doc2dial, a new dataset of goal-oriented dialogues that are grounded in the associated documents. Inspired by how the authors compose documents for guiding end users,…
Multi-task Learning with Multi-head Attention for Multi-choice Reading Comprehension
Hui Wan
Multiple-choice Machine Reading Comprehension (MRC) is an important and challenging Natural Language Understanding (NLU) task, in which a machine must choose the answer to a questi…