Recent text generation research has increasingly focused on open-ended domains such as
story and poetry generation. Because models built for such tasks are difficult to evaluate …

We present a new dataset containing 10K human-annotated games of Go and show how
these natural language annotations can be used as a tool for model interpretability. Given a …

Despite many recent advancements in language modeling, state-of-the-art language models
lack grounding in the real world and struggle with tasks involving complex reasoning …

Deep learning-based expert models have reached superhuman performance in decision-
making domains such as chess and Go. However, it is under-explored to explain or …

Text-to-text transformers have shown remarkable success in the task of multi-task transfer
learning, especially in natural language processing (NLP). However, while there have been …

In this study, we propose a gradient-based saliency map generation method to improve the
explainability of saliency maps in two-player board games, such as chess and shogi …

This paper presents a rap-style commentary system for enhancing audience participation
games. In this work, an audience participation fighting game played by two AI players is …

State-of-the-art game playing programs do not provide an explanation for their move choice
beyond a numerical score for the best and alternative moves. However, human players want …

Playing video games has been popular across all the age limits of modern society. In the
beginning, it was limited among the younger community and it was just a hobby limited to …

Video games evolved into competitive sports within a short span of time. Commentary plays
a key role in any sport. Commentary is useful to understand the game as well as to capture …