Generating Unambiguous and Diverse Referring Expressions
Journal Article
Panagiaris, N., Hart, E., & Gkatzia, D. (2021)
Generating Unambiguous and Diverse Referring Expressions . Computer Speech and Language, 68, https://doi.org/10.1016/j.csl.2020.101184
Neural Referring Expression Generation (REG) models have shown promising results in generating expressions which uniquely describe visual objects. However, current REG models ...
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training
Conference Proceeding
Panagiaris, N., Hart, E., & Gkatzia, D. (2020)
Improving the Naturalness and Diversity of Referring Expression Generation models using Minimum Risk Training. In Proceedings of the 13th International Conference on Natural Language Generation. , (41-51
In this paper we consider the problem of optimizing neural Referring Expression Generation (REG) models with sequence level objectives. Recently reinforcement learning (RL) te...