16 citations · 48 across the 21 of their papers we have counts for
4 papers · 2 filters
Out-of-Task Training for Dialog State Tracking Models
Michael Heck, Carel van Niekerk, Nurul Lubis +4
Dialog state tracking (DST) suffers from severe data sparsity. While many natural language processing (NLP) tasks benefit from transfer learning and multi-task learning, in dialog…
LAVA: Latent Action Spaces via Variational Auto-encoding for Dialogue Policy Optimization
Nurul Lubis, Christian Geishauser, Michael Heck +4
Reinforcement learning (RL) can enable task-oriented dialogue systems to steer the conversation towards successful task completion. In an end-to-end setting, a response can be cons…
Knowing What You Know: Calibrating Dialogue Belief State Distributions via Ensembles
Carel van Niekerk, Michael Heck, Christian Geishauser +4
The ability to accurately track what happens during a conversation is essential for the performance of a dialogue system. Current state-of-the-art multi-domain dialogue state track…
TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking
Michael Heck, Carel van Niekerk, Nurul Lubis +4
Task-oriented dialog systems rely on dialog state tracking (DST) to monitor the user's goal during the course of an interaction. Multi-domain and open-vocabulary settings complicat…