← Search

Huifang Du

2 accepted papers

2024

Rewarding What Matters: Step-by-Step Reinforcement Learning for Task-Oriented Dialogue

EMNLP 2024finding

Reinforcement learning (RL) is a powerful approach to enhance task-oriented dialogue (TOD) systems. However, existing RL methods tend to mainly focus on generation tasks, such as dialogue policy learning (DPL) or response generation (RG), while neglecting dialogue state tracking (DST) for understand…

Cited by 1SourcePDFScholar
2024

Towards Proactive Interactions for In-Vehicle Conversational Assistants Utilizing Large Language Models

IJCAI 2024poster

Research demonstrates that the proactivity of in-vehicle conversational assistants (IVCAs) can help to reduce distractions and enhance driving safety, better meeting users' cognitive needs. However, existing IVCAs struggle with user intent recognition and context awareness, which leads to suboptimal…