5 papers · 1 filter
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…
Pre-Finetuning for Few-Shot Emotional Speech Recognition
Maximillian Chen, Zhou Yu
Speech models have long been known to overfit individual speakers for many classification tasks. This leads to poor generalization in settings where the speakers are out-of-domain…
VarBench: Robust Language Model Benchmarking Through Dynamic Variable Perturbation
Kun Qian, Shunji Wan, Claudia Tang +4
As large language models achieve impressive scores on traditional benchmarks, an increasing number of researchers are becoming concerned about benchmark data leakage during pre-tra…