arXiv AI June 9, 2026 By Luoyuan Zhang, Bokai Xu, Junbo Cui, Weiyue Sun, Yingjing Xu, Hanyu Liu, Yuan Yao

Liberating LLM Capabilities in Full-Duplex Speech Models

arXiv:2606. 07547v1 Announce Type: cross Abstract: Speech-based large language models are typically constrained to spoken replies, which limits their user-facing outputs to what can be verbalized and suppresses text-native capabilities such as code generation, structured analysis, and multi-step reasoning in realtime interaction, for tasks that require persistent, structured, and inspectable intermediate outputs.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 11

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

arXiv:2606. 11386v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the internal mechanism by which they coordinate listening and speaking remains underexplored.

By Cheng-Kuang Chang, Kai-Wei Chang, Alexander H. Liu, James Glass

llms fine-tuning benchmarks

arXiv AI

Jun 4

Audio Interaction Model

arXiv:2606. 05121v1 Announce Type: cross Abstract: Audio is an inherently interactive modality, yet today's Large Audio Language Models (LALMs) are offline, and streaming audio models each handle only a single task such as streaming ASR or voice chatting.

By Zhifei Xie, Zihang Liu, Ze An, Xiaobin Hu, Yue Liao, Ziyang Ma, Dongchao Yang, Mingbao Lin, Deheng Ye, Shuicheng Yan, Chunyan Miao

llms multimodal benchmarks

arXiv AI

Jun 15

Chronological Thinking in Full-Duplex Spoken Dialogue Language Models

arXiv:2510. 05150v3 Announce Type: replace-cross Abstract: 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 speech streams while generating responses.

By Donghang Wu, Haoyang Zhang, Chen Chen, Tianyu Zhang, Fei Tian, Xuerui Yang, Gang Yu, Hexin Liu, Nana Hou, Yuchen Hu, Eng Siong Chng

llms agents

arXiv AI

Aug 11

PACE: A Playback-Aligned Context Engine for LLM-Based Full-Duplex Voice Dialogue

arXiv:2608. 07631v1 Announce Type: cross Abstract: LLM-based full-duplex voice services allow users to speak while the assistant is responding.

By Shibo Wang, Zicheng Zhang, Libo Wang, Junfeng Ma

llms benchmarks

arXiv AI

Jun 26

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

arXiv:2606. 25041v2 Announce Type: replace-cross Abstract: We present Wan-Streamer, a native-streaming, end-to-end interactive foundation model designed from the ground up for real-time, low-latency, full-duplex audio-visual interaction.

By Lianghua Huang, Zhi-Fan Wu, Wei Wang, Yupeng Shi, Mengyang Feng, Junjie He, Chen-Wei Xie, Yu Liu, Jingren Zhou, Ang Wang, Bang Zhang, Baole Ai, Chen Liang, Cheng Yu, Chongyang Zhong, Jinwei Qi, Kai Zhu, Pandeng Li, Peng Zhang, Wenyuan Zhang, Xinhua Cheng, Yitong Huang, Yun Zheng, Zoubin Bi

llms multimodal

arXiv AI

Aug 12

Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence

arXiv:2608. 10720v1 Announce Type: new Abstract: Omni-modal dialogue models can understand multimodal inputs and synthesize spoken replies, yet their responses remain visually disembodied.

By Haoyu Zhang, Zhipeng Li, Xiaoying Tang, Tianshu Yu, Yiwen Guo

multimodal

Related stories

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

Audio Interaction Model

Chronological Thinking in Full-Duplex Spoken Dialogue Language Models

PACE: A Playback-Aligned Context Engine for LLM-Based Full-Duplex Voice Dialogue

Wan-Streamer v0.1: End-to-end Real-time Interactive Foundation Models

Ex-Omni-2D: Expressive Omni-Modal Dialogue Models with Native Visual Presence