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README.md
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[📄 Paper](https://arxiv.org/abs/2606.14777) · [🌐 Project Page & Demos](https://joyai-vl-video-future-academy-jd.github.io/JoyAI-VL-Interaction/) · [💻 GitHub](https://github.com/jd-opensource/JoyAI-VL-Interaction) · [🤗 Paper Page](https://huggingface.co/papers/2606.14777)
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[📄 Paper](https://arxiv.org/abs/2606.14777) · [🌐 Project Page & Demos](https://joyai-vl-video-future-academy-jd.github.io/JoyAI-VL-Interaction/) · [💻 GitHub](https://github.com/jd-opensource/JoyAI-VL-Interaction) · [🤗 Paper Page](https://huggingface.co/papers/2606.14777)
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---
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## Overview
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Most large models today are **turn-based**: they answer only when you ask. But many moments in the real world don't wait for a question — a fire starts on a security feed, someone falls, a product flashes by in a livestream. Once missed, the moment is gone.
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**JoyAI-VL-Interaction** is built for exactly these moments. It is an **8B-scale, vision-first interaction model** that continuously watches a live video stream and, **every second, decides on its own** to take one of three actions:
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- **Speak** — respond when something is worth saying
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- **Stay silent** — keep watching when nothing warrants a response (a first-class, trained action)
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- **Delegate** — hand a hard subtask to a background model/agent, keep watching, and weave the result back in when it returns
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The decision of *when to act* is **learned inside the model** (from second-by-second time-aligned data + RL), not bolted on by an external turn-detector or polling loop. Vision is the first-class driver; speech (ASR/TTS) is treated as pluggable I/O.
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To our knowledge, this is the **first open, vision-driven interaction model** released together with its training recipe, data, and a complete deployable system.
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