EvidenceConnect

Headlines · 2

1. 2d
   InclusionAI releases ZwZ2 multimodal model family

   InclusionAI released ZwZ2, a Qwen-based model family with 27B, 9B, and 4B variants designed to connect visual evidence across image regions through comparison, aggregation, matching, and multi-step reasoning. The model summary says training uses full images and inference requires no zooming tools. Its EvidenceConnect dataset contains verified multi-region questions constructed from SA-1B images, with answers checked through cross-model agreement and drop-one-region tests. According to InclusionAI, ZwZ2-27B outperformed its base model on all 25 benchmarks across six domains, raising overall accuracy from 55.52 to 60.51.

   r/LocalLLaMA · 🔥 2
2. 5d
   EvidenceConnect trains VLMs to connect visual evidence

   Lai Wei and 12 other authors submitted “Zooming without Zooming v2” to arXiv on October 27, 2026, introducing EvidenceConnect, a synthetic-data framework built around zoomed views of related regions in single images. The authors train base vision-language models on questions requiring visual-evidence comparison, aggregation, or chaining using RLVR, producing Zooming without Zooming v2 (ZwZ2). They report gains in fine-grained and spatial perception, embodied spatial reasoning, multimodal long-context understanding, multimodal agent tasks, and general visual reasoning.

   Hugging Face · Papers · 🔥 0

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