Spoken Language Understanding (SLU) aims to extract the semantics frame of user queries,
which is a core component in a task-oriented dialog system. With the burst of deep neural …

Open intent classification is a challenging task in dialogue systems. On the one hand, it
should ensure the quality of known intent identification. On the other hand, it needs to detect …

Discovering new intents is a crucial task in dialogue systems. Most existing methods are
limited in transferring the prior knowledge from known intents to new intents. These methods …

Program synthesis from input-output (IO) examples has been a long-standing challenge.
While recent works demonstrated limited success on domain-specific languages (DSL), it …

Consumption intent, defined as the decision-driven force of consumption behaviors, is
crucial for improving the explainability and performance of user-modeling systems, with …

Dialogue State Tracking (DST) module is an essential component of task-oriented dialog
systems to understand users' goals and needs. Collecting dialogue state labels including …

Carefully-designed schemas describing how to collect and annotate dialog corpora are a
prerequisite towards building task-oriented dialog systems. In practical applications …

Abstract New Intent Discovery (NID) strives to identify known and reasonably deduce novel
intent groups in the open-world scenario. But current methods face issues with inaccurate …

The challenge of defining a slot schema to represent the state of a task-oriented dialogue
system is addressed by Slot Schema Induction (SSI), which aims to automatically induce …

Out-of-Domain (OOD) intent classification is an important task for a dialog system, as it
allows for appropriate responses to be generated. Previous studies aiming to solve the OOD …