Derek Chen is a Research Scientist at ASAPP designing intelligent dialogue systems with stronger natural language understanding capabilities. He received his Masters in Computer Science from the University of Washington and his undergraduate degree from UC Berkeley. His research is focused on data efficiency methods including active learning, data augmentation and meta-learning. He is also interested in techniques surrounding uncertainty measurement so that a dialogue agent can better manage ambiguity and out-of-scope situations.
GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation
New ASAPP research introduces an orthogonal technique that augments existing data to train better out of scope detectors operating in low-data regimes. Read more
Task-oriented dialogue systems could be better. Here’s a new dataset to help.
Dialogue State Tracking has run its course. That’s why we’re establishing a new Action-Based Conversations Dataset. Read more