Building dialogue systems requires a large corpus of annotated dialogues. Such datasets
are usually created via crowdsourcing, which is expensive and time-consuming. In this …

Dialogue understanding tasks often necessitate abundant annotated data to achieve good
performance and that presents challenges in low-resource settings. To alleviate this barrier …

This paper explores interactive facial image editing via dialogue and introduces the ChatEdit
benchmark dataset for evaluating image editing and conversation abilities in this context …

Natural Language Understanding (NLU) is a core task when building conversational agents,
fulfilling the objectives of understanding the user's goal and detecting any valuable …

Building task-oriented dialogue systems for solving specific tasks within companies
represents a challenging research objective especially when the specific expertise of the …

Training data has played a major role in the rise of large deep learning models. In particular,
the scale and diversity of training data has led to incredible new capabilities in large …

References 1. J. Andreas, J. Bufe, D. Burkett, C. Chen, J. Clausman, J. Crawford, K. Crim, J.
DeLoach, L. Dorner, J. Eisner, H. Page 1 IGA & SILAGHI ONTOLOGY-BASED DIALOGUE …