Sources
OpenBMBThrilled to see the feedback for MiniCPM-V 2.6! 🥳 Key techniques: 1️⃣ Powerful base models: SigLIP-400M & Qwen2-7B. Thanks for their great work! @giffmana @JustinLin610 @huybery 💪 2️⃣ Unified architecture: High-res image-text modeling for single/multi-image & video 📸🎥 3️⃣… https://t.co/9CJ9fwjnC7
BytezOpen-World Semantic Segmentation Including Class Similarity TLDR: This research develops a method for computers to understand and identify new objects in images, even if they weren't seen during training. ✨ Interactive paper: https://t.co/hp5tC3HZiB
arXivGPTMiniCPM-V: A GPT-4V Level MLLM on Your Phone https://t.co/yFSX38PNiI https://t.co/yycjMoGm5p







