53 citations · 169 across the 9 of their papers we have counts for
11 papers
Overview of the Ninth Dialog System Technology Challenge: DSTC9
Chulaka Gunasekara, Seokhwan Kim, Luis Fernando D'Haro +36
This paper introduces the Ninth Dialog System Technology Challenge (DSTC-9). This edition of the DSTC focuses on applying end-to-end dialog technologies for four distinct tasks in…
Video Question Answering on Screencast Tutorials
Wentian Zhao, Seokhwan Kim, Ning Xu +1
This paper presents a new video question answering task on screencast tutorials. We introduce a dataset including question, answer and context triples from the tutorial videos for…
Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access
Seokhwan Kim, Mihail Eric, Karthik Gopalakrishnan +3
Most prior work on task-oriented dialogue systems are restricted to a limited coverage of domain APIs, while users oftentimes have domain related requests that are not covered by t…
Policy-Driven Neural Response Generation for Knowledge-Grounded Dialogue Systems
Behnam Hedayatnia, Karthik Gopalakrishnan, Seokhwan Kim +3
Open-domain dialogue systems aim to generate relevant, informative and engaging responses. Seq2seq neural response generation approaches do not have explicit mechanisms to control…
Just Ask:An Interactive Learning Framework for Vision and Language Navigation
Ta-Chung Chi, Mihail Eric, Seokhwan Kim +2
In the vision and language navigation task, the agent may encounter ambiguous situations that are hard to interpret by just relying on visual information and natural language instr…
TutorialVQA: Question Answering Dataset for Tutorial Videos
Anthony Colas, Seokhwan Kim, Franck Dernoncourt +3
Despite the number of currently available datasets on video question answering, there still remains a need for a dataset involving multi-step and non-factoid answers. Moreover, rel…
The Eighth Dialog System Technology Challenge
Seokhwan Kim, Michel Galley, Chulaka Gunasekara +18
This paper introduces the Eighth Dialog System Technology Challenge. In line with recent challenges, the eighth edition focuses on applying end-to-end dialog technologies in a prag…
Analyzing Sentence Fusion in Abstractive Summarization
Logan Lebanoff, John Muchovej, Franck Dernoncourt +4
While recent work in abstractive summarization has resulted in higher scores in automatic metrics, there is little understanding on how these systems combine information taken from…
Scoring Sentence Singletons and Pairs for Abstractive Summarization
Logan Lebanoff, Kaiqiang Song, Franck Dernoncourt +4
When writing a summary, humans tend to choose content from one or two sentences and merge them into a single summary sentence. However, the mechanisms behind the selection of one o…
Neural Sentence Embedding using Only In-domain Sentences for Out-of-domain Sentence Detection in Dialog Systems
Seonghan Ryu, Seokhwan Kim, Junhwi Choi +2
To ensure satisfactory user experience, dialog systems must be able to determine whether an input sentence is in-domain (ID) or out-of-domain (OOD). We assume that only ID sentence…
A Discourse-Aware Attention Model for Abstractive Summarization of Long Documents
Arman Cohan, Franck Dernoncourt, Doo Soon Kim +4
Neural abstractive summarization models have led to promising results in summarizing relatively short documents. We propose the first model for abstractive summarization of single,…