134 citations · 257 across the 9 of their papers we have counts for
6 papers · 1 filter
Characterizing Sources of Uncertainty to Proxy Calibration and Disambiguate Annotator and Data Bias
Asma Ghandeharioun, Brian Eoff, Brendan Jou +1
Supporting model interpretability for complex phenomena where annotators can legitimately disagree, such as emotion recognition, is a challenging machine learning task. In this wor…
Hierarchical Reinforcement Learning for Open-Domain Dialog
Abdelrhman Saleh, Natasha Jaques, Asma Ghandeharioun +2
Open-domain dialog generation is a challenging problem; maximum likelihood training can lead to repetitive outputs, models have difficulty tracking long-term conversational goals,…
Towards Understanding Emotional Intelligence for Behavior Change Chatbots
Asma Ghandeharioun, Daniel McDuff, Mary Czerwinski +1
A natural conversational interface that allows longitudinal symptom tracking would be extremely valuable in health/wellness applications. However, the task of designing emotionally…
Engineering Music to Slow Breathing and Invite Relaxed Physiology
Grace Leslie, Asma Ghandeharioun, Diane Y. Zhou +1
We engineered an interactive music system that influences a user's breathing rate to induce a relaxation response. This system generates ambient music containing periodic shifts in…
Way Off-Policy Batch Deep Reinforcement Learning of Implicit Human Preferences in Dialog
Natasha Jaques, Asma Ghandeharioun, Judy Hanwen Shen +5
Most deep reinforcement learning (RL) systems are not able to learn effectively from off-policy data, especially if they cannot explore online in the environment. These are critica…
Approximating Interactive Human Evaluation with Self-Play for Open-Domain Dialog Systems
Asma Ghandeharioun, Judy Hanwen Shen, Natasha Jaques +4
Building an open-domain conversational agent is a challenging problem. Current evaluation methods, mostly post-hoc judgments of static conversation, do not capture conversation qua…