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Paper · arXiv

DuplexAct: How Interactive Are Frontier Full-Duplex Spoken Language Models?

End-to-end (E2E) full-duplex spoken language models (FD-SLMs) enable simutanous listening and speaking continously, requiring models to take appropriate interaction actions as conversations unfold. However, existing benchmarks lack a structured action-level formulation, often evaluate action occurrence rather than success, and provide limited coverage of diverse real-world conversations. We introduce DuplexAct, a benchmark for evaluating interaction action taking in E2E FD-SLMs. DuplexAct defines a three-level action taxonomy spanning eight interaction actions and 24 corresponding interaction conditions. We further characterize successful action-taking through immediate execution and subs...

AuthorsJiaheng Dong, Shihong Tan, Gongping Huang et al.
Primary categorycs.AI
Published13 October 2026
Last updated at source13 October 2026
cs.AI
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