9
In this work we consider the problem of confounding in offline RL, also referred to as the delusion problem. While it is known that …
End-to-end interactive learning of dialogue systems has been all-but-abandoned in favour of other approaches using more labelled data, …
The ALFRED environment features an embodied agent following instructions and accomplishing tasks in simulated home environments. …
Continual learning (CL) aims to design algorithms that can learn from non-stationarystreams of stationary tasks without forgetting. …
Data augmentation is a widely employed technique to alleviate the problem of data scarcity. In this work, we propose a prompting-based …
We outline three research directions towards the practical implementation of explainable, sensible and virtuous chatbots for the …
Black-box machine learning (ML) models have become increasingly popular in practice. They can offer great performance, especially in …
In this work, we introduce models that perform comparably with state-of-the-art alternatives in terms of prediction accuracy while …
As producing high-quality summaries of chat dialogues currently requires large labeled datasets, we propose a method to efficiently …
The estimation of time-varying quantities is a fundamental component of decision making in fields such as healthcare and finance. …