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20212026
most citedFunAudioLLM: Voice Understanding and Generation Foundation Models for Natural Interaction Between Humans and LLMs

9 citations · 25 across the 23 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

eess.AS2026

Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction

Lujia Bao, Qian Chen, Luyao Cheng +15

Real-time voice assistants must reason over evolving requests, execute actions, and follow conversational rules. Qwen-Audio-3.1-Realtime brings these requirements together through…

eess.AS2026

Qwen-Audio-Agent Technical Report

Chong Deng, Yunjie Ji, Yuxiang Kong +5

We present Qwen-Audio-Agent, a harness that combines full-duplex voice interaction with asynchronous task execution through a foreground-background architecture. A Frontend Agent m…

cs.CL2026

Enabling Proactive Spoken Turns via a Generalized Style-Aware Full-Duplex Framework

Tianrui Pan, Qinglin Zhang, Chong Deng +6

Compared with half-duplex dialogue systems where the system waits for user turn completion before it responds, natural full-duplex dialogue systems require agents to act proactivel…

cs.CL2026

GenesisFunc: Multi-Agent Data Generation for Accurate and Generalizable Function-Calling

Hao-Xiang Xu, Chong Deng, Jiaqing Liu +5

Large Language Models (LLMs) extend their capabilities through function-calling (FC), which relies on training data with high quality, diversity, and broad coverage of scenario. Ho…

cs.LG2026

FGGM: Fisher-Guided Gradient Masking for Continual Learning

Chao-Hong Tan, Qian Chen, Wen Wang +6

Catastrophic forgetting impairs the continuous learning of large language models. We propose Fisher-Guided Gradient Masking (FGGM), a framework that mitigates this by strategically…

cs.CL2026★ 1 cited

Fun-Audio-Chat Technical Report

Tongyi Fun Team, Qian Chen, Luyao Cheng +10

Recent advancements in joint speech-text models show great potential for seamless voice interactions. However, existing models face critical challenges: temporal resolution mismatc…