97 citations · 133 across the 4 of their papers we have counts for
5 papers
DialoGLUE: A Natural Language Understanding Benchmark for Task-Oriented Dialogue
Shikib Mehri, Mihail Eric, Dilek Hakkani-Tur
A long-standing goal of task-oriented dialogue research is the ability to flexibly adapt dialogue models to new domains. To progress research in this direction, we introduce DialoG…
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…
SceneSeer: 3D Scene Design with Natural Language
Angel X. Chang, Mihail Eric, Manolis Savva +1
Designing 3D scenes is currently a creative task that requires significant expertise and effort in using complex 3D design interfaces. This effortful design process starts in stark…