Natural Language Processing
As producing high-quality summaries of chat dialogues currently requires large labeled datasets, we propose a method to efficiently …
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 embodied instruction following tasks in simulated home environments. However, end-to-end deep learning …
Data augmentation alleviates the problem of data scarcity when training language models (LMs) by generating new examples based on the …
Geoscientists use observations and descriptions of the rock record to study the origins and history of our planet, which has resulted …
Large pre-trained language models for textual data have an unconstrained output space; at each decoding step, they can produce any of …
In a conversational question answering scenario, a questioner seeks to extract information about a topic through a series of …
Recent neural text-to-SQL models can effectively translate natural language questions to corresponding SQL queries on unseen databases. …
Negation is a core construction in natural language. Despite being very successful on many tasks, state-of-the-art pre-trained language …
Multi-Task Learning (MTL) networks have emerged as a promising method for transferring learned knowledge across different tasks. …