We introduce Korean Language Understanding Evaluation (KLUE) benchmark. KLUE is a
collection of 8 Korean natural language understanding (NLU) tasks, including Topic …

While communicating with a user, a task-oriented dialogue system has to track the user's
needs at each turn according to the conversation history. This process called dialogue state …

Recently, pre-training methods have shown remarkable success in task-oriented dialog
(TOD) systems. However, most existing pre-trained models for TOD focus on either dialog …

Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented
dialogue in unseen domains without the expense of collecting in-domain data. In this paper …

The MultiWOZ 2.0 dataset has greatly stimulated the research of task-oriented dialogue
systems. However, its state annotations contain substantial noise, which hinders a proper …

Controllable text generation concerns two fundamental tasks of wide applications, namely
generating text of given attributes (ie, attribute-conditional generation), and minimally editing …

Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety
of task-oriented dialogue domains without the expense of collecting in-domain data. In this …

Annotating task-oriented dialogues is notorious for the expensive and difficult data collection
process. Few-shot dialogue state tracking (DST) is a realistic solution to this problem. In this …

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 …

Pre-training methods with contrastive learning objectives have shown remarkable success
in dialog understanding tasks. However, current contrastive learning solely considers the …