InclusionAI 发布 ZwZ2 多模态模型系列
AI 总结
InclusionAI 发布了基于 Qwen 的 ZwZ2 系列，包含 27B、9B 和 4B 版本，旨在通过比较、聚合、匹配和多步推理连接图像不同区域的视觉证据。模型摘要称，训练使用完整图像，推理时无需缩放工具。其 EvidenceConnect 数据集包含基于 SA-1B 图像构建的经过验证的多区域问题，并通过跨模型一致性和去除单个区域测试检查答案。据 InclusionAI 称，ZwZ2-27B 在六个领域的 25 项基准中均优于基础模型，总体准确率从 55.52 提升至 60.51。
深度见解
ZwZ2 提供三种规模的 Qwen 衍生模型，用于基于完整图像且无需推理时缩放的多区域视觉推理。据 InclusionAI 报告，相关提升覆盖细粒度感知、空间推理、长上下文理解、多模态智能体和通用视觉推理。
| ✨ Model Summary ZwZ2-27B is the Qwen3.6-27B-based model in Zooming-without-Zooming-v2 (ZwZ2). It learns to connect visual evidence across regions through comparison, aggregation, matching, and multi-step reasoning. Training uses full images; inference requires no zooming tools. On 25 benchmarks across six domains, it improves over its base model on every benchmark, increasing overall accuracy from 55.52 to 60.51 (+4.99 points). Gains extend from fine-grained perception to spatial reasoning, long-context understanding, multimodal agents, and general visual reasoning. ⚙️ Method and Data EvidenceConnect builds verified multi-region questions from SA-1B images: All three model sizes use approximately 20K training examples. The policy sees full images with colored region outlines; privileged crop layouts are used only for data construction. See ZwZ2-RL-VQA for the data schema and synthesis process. Processing img eup6n3gb9lyh1... Processing img amts18kd9lyh1... https://huggingface.co/inclusionAI/ZwZ2-27B-GGUF https://huggingface.co/inclusionAI/ZwZ2-9B-GGUF https://huggingface.co/inclusionAI/ZwZ2-4B-GGUF submitted by /u/jacek2023 [link] [comments] |
#InclusionAI#ZwZ2#Qwen#Qwen3.6-27B#EvidenceConnect#SA-1B#ZwZ2-RL-VQA