collaborators

10 papers

cs.AI2026

Just A Rather Very Intelligent Spoken Agent

Chen Chen, Zhehuai Chen

Long-horizon AI agents are becoming increasingly capable, yet their interaction with users remains surprisingly thin. In most workflows, users give an initial instruction, receive…

eess.AS2026

Decoupling Conversational Dynamics in Full-Duplex Spoken Models through Reinforcement Learning

Yuxin Li, Donghang Wu, Guan-Ting Lin +4

Recent full-duplex spoken dialogue models have demonstrated compelling progress toward human-like interaction, enabling agents to respond with low latency, produce backchannels, an…

cs.CL2026

Chronological Thinking in Full-Duplex Spoken Dialogue Language Models

Donghang Wu, Haoyang Zhang, Chen Chen +8

Recent advances in spoken dialogue language models (SDLMs) reflect growing interest in shifting from turn-based to full-duplex systems, where the models continuously perceive user…

eess.AS2026

The Silent Thought: Modeling Internal Cognition in Full-Duplex Spoken Dialogue Models via Latent Reasoning

Donghang Wu, Tianyu Zhang, Yuxin Li +4

During conversational interactions, humans subconsciously engage in concurrent thinking while listening to a speaker. Although this internal cognitive processing may not always man…

eess.AS2026

Full-Duplex-Bench-v3: Benchmarking Tool Use for Full-Duplex Voice Agents Under Real-World Disfluency

Guan-Ting Lin, Chen Chen, Zhehuai Chen +1

We introduce Full-Duplex-Bench-v3 (FDB-v3), a benchmark for evaluating spoken language models under naturalistic speech conditions and multi-step tool use. Unlike prior work, our d…

cs.CL2026

Attributing Response to Context: A Jensen-Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation

Ruizhe Li, Chen Chen, Yuchen Hu +3

Retrieval-Augmented Generation (RAG) leverages large language models (LLMs) combined with external contexts to enhance the accuracy and reliability of generated responses. However,…