10 citations · 10 across the 2 of their papers we have counts for
4 papers
DELPHI: Data for Evaluating LLMs' Performance in Handling Controversial Issues
David Q. Sun, Artem Abzaliev, Hadas Kotek +3
Controversy is a reflection of our zeitgeist, and an important aspect to any discourse. The rise of large language models (LLMs) as conversational systems has increased public reli…
Intelligent Assistant Language Understanding On Device
Cecilia Aas, Hisham Abdelsalam, Irina Belousova +20
It has recently become feasible to run personal digital assistants on phones and other personal devices. In this paper we describe a design for a natural language understanding sys…
Feedback Effect in User Interaction with Intelligent Assistants: Delayed Engagement, Adaption and Drop-out
Zidi Xiu, Kai-Chen Cheng, David Q. Sun +7
With the growing popularity of intelligent assistants (IAs), evaluating IA quality becomes an increasingly active field of research. This paper identifies and quantifies the feedba…
Sample-efficient Deep Reinforcement Learning for Dialog Control
Kavosh Asadi, Jason D. Williams
Representing a dialog policy as a recurrent neural network (RNN) is attractive because it handles partial observability, infers a latent representation of state, and can be optimiz…