53 citations · 120 across the 7 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…