4 papers
ThoughtTrace: Understanding User Thoughts in Real-World LLM Interactions
Chuanyang Jin, Binze Li, Haopeng Xie +6
Conversational AI has now reached billions of users, yet existing datasets capture only what people say, not what they think. We introduce ThoughtTrace, the first large-scale datas…
MIST: Multimodal Interactive Speech-based Tool-calling Conversational Assistants for Smart Homes
Maximillian Chen, Xuanming Zhang, Michael Peng +3
The rise of Internet of Things (IoT) devices in the physical world necessitates voice-based interfaces capable of handling complex user experiences. While modern Large Language Mod…
Learning to Clarify: Multi-turn Conversations with Action-Based Contrastive Self-Training
Maximillian Chen, Ruoxi Sun, Tomas Pfister +1
Large language models (LLMs), optimized through human feedback, have rapidly emerged as a leading paradigm for developing intelligent conversational assistants. However, despite th…
Bottom-Up Synthesis of Knowledge-Grounded Task-Oriented Dialogues with Iteratively Self-Refined Prompts
Kun Qian, Maximillian Chen, Siyan Li +2
Training conversational question-answering (QA) systems requires a substantial amount of in-domain data, which is often scarce in practice. A common solution to this challenge is t…