16 citations · 60 across the 15 of their papers we have counts for
17 papers
Affect Recognition in Conversations Using Large Language Models
Shutong Feng, Guangzhi Sun, Nurul Lubis +3
Affect recognition, encompassing emotions, moods, and feelings, plays a pivotal role in human communication. In the realm of conversational artificial intelligence, the ability to…
From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialogue
Shutong Feng, Nurul Lubis, Benjamin Ruppik +6
Emotion recognition in conversations (ERC) is a crucial task for building human-like conversational agents. While substantial efforts have been devoted to ERC for chit-chat dialogu…
EmoUS: Simulating User Emotions in Task-Oriented Dialogues
Hsien-Chin Lin, Shutong Feng, Christian Geishauser +6
Existing user simulators (USs) for task-oriented dialogue systems only model user behaviour on semantic and natural language levels without considering the user persona and emotion…
ChatGPT for Zero-shot Dialogue State Tracking: A Solution or an Opportunity?
Michael Heck, Nurul Lubis, Benjamin Ruppik +6
Recent research on dialogue state tracking (DST) focuses on methods that allow few- and zero-shot transfer to new domains or schemas. However, performance gains heavily depend on a…
ConvLab-3: A Flexible Dialogue System Toolkit Based on a Unified Data Format
Qi Zhu, Christian Geishauser, Hsien-chin Lin +10
Task-oriented dialogue (TOD) systems function as digital assistants, guiding users through various tasks such as booking flights or finding restaurants. Existing toolkits for build…
Dialogue Evaluation with Offline Reinforcement Learning
Nurul Lubis, Christian Geishauser, Hsien-Chin Lin +4
Task-oriented dialogue systems aim to fulfill user goals through natural language interactions. They are ideally evaluated with human users, which however is unattainable to do at…