arXiv Machine Learning By Krish Agarwal, Zhuoming Chen, Yanyuan Qin, Zhenyu Gu, Atri Rudra, Beidi Chen

FlashRT: Agent Harness for Guiding Agents to Deploy Real-Time Multimodal Applications

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arXiv:2607. 18171v1 Announce Type: new Abstract: Real-time multimodal applications, including voice agents and interactive video generation, compose heterogeneous models into pipelines whose efficient deployment requires application-specific decisions about placement, streaming, and intra-model parallelism.

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arXiv Computation and Language
Sep 23

Qwen3.8-Omni: Towards Native Omni-Modal Agents

Qwen3.8-Omni-Flash is a natively multimodal agentic model designed for real‑world multimodal productivity, offering enhanced multimodal understanding, reasoning, and long‑horizon agentic task performance. It builds on a sparse mixture‑of‑experts architecture, extends its context window to one million tokens, and supports long‑context multimodal reasoning and planning. The release includes Qwen-MM-Plugins for native audio and video support and Qwen-Live-Harness for building responsive, real‑time multimodal agents, with extensive evaluations confirming strong performance across multimodal tasks.

By Qwen Team