NYU researchers have introduced Cambrian-1, a fully open, vision-centric exploration of multimodal large language models (MLLMs). Cambrian-1 is designed to enhance visual representations in AI, setting a new standard in the field. This project includes open datasets, models, and source code, and introduces a new vision-centric benchmark called CV-Bench. Cambrian-1 achieves state-of-the-art (SotA) performance and serves as a comprehensive, open cookbook for instruction-tuned MLLMs. The project emphasizes the importance of shifting focus from scaling language models to enhancing visual representations, aiming to improve real-world performance and integration. A key feature of Cambrian-1 is the Spatial Vision Aggregator, which enhances how AI understands visuals.
NYU Researchers Introduce Cambrian-1: Advancing Multimodal AI with Vision-Centric Large Language Models (#LLMs) for Enhanced Real-World Performance and Integration https://t.co/I7IHDgOtTi
Cambrian-1: an open project on vision-centric multimodal LLMs. Open datasets, open models, open source. Extensive comparisons: visual encoders,connector designs, instruction tuning data, instruction tuning recipes. New vision-centric benchmark. CV-Bench. By a large cast of… https://t.co/Z2r2Gzh1bT
NYU Researchers Introduce Cambrian-1: Advancing Multimodal AI with Vision-Centric Large Language Models for Enhanced Real-World Performance and Integration Traditionally, visual representations in AI are evaluated using benchmarks such as ImageNet for image classification or… https://t.co/x3ukX0eviF
Cambrian-1 A Fully Open, Vision-Centric Exploration of Multimodal LLMs ◼ 🔍Cambrian-1, a new family of multimodal LLMs, excels in blending vision-centric tech with language models. Its unique Spatial Vision Aggregator enhances how AI understands visuals, setting a new standard… https://t.co/VskTeDKRXn
Introducing Cambrian-1, a fully open project from our group at NYU. The world doesn't need another MLLM to rival GPT-4V. Cambrian is unique as a vision-centric exploration & here's why I think it's time to shift focus from scaling LLMs to enhancing visual representations.🧵[1/n] https://t.co/RyIHb2jvSl
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs Web: https://t.co/WwE9DgVIy8 Abs: https://t.co/U6HtSDxkFm Introduce Cambrian-1, a family of multimodal LLMs (MLLMs) designed with a vision-centric approach and a new vision-centric benchmark, CV-Bench https://t.co/o3y9r0iQ4W
Video-Infinity: Distributed Long Video Generation Can generate super long videos, up to 2300 frames within 5 mins by Clip parallelism and Dual-scope attention proj: https://t.co/7ywX3pY4h9 abs: https://t.co/CUkAGG8RSn repo: https://t.co/PdR05xhyrj https://t.co/qWrREC09vL
🔥Long Context from Langugae to Vision🔥 #LongVA can process 2000 frames or over 200K visual tokens with SoTA performance on Video-MME among 7B models - Paper: https://t.co/iCVi2EISeB - Code: https://t.co/Jb7P5F59Bf - Demo @Gradio: https://t.co/BYyiXj8pc2 . Thanks to @_akhaliq! https://t.co/ZBdWx4HrlG
Long Context Transfer from Language to Vision - Can process 2000 frames or over 200K visual tokens - SotA perf on VideoMME among 7B-scale models abs: https://t.co/JlXz5TPbVP repo: https://t.co/Nyi6fTS5qh https://t.co/ehRr5V0syo
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs Achieves SotA performances and serves as a comprehensive, open cookbook for instruction-tuned MLLMs proj: https://t.co/QOlAsrK010 abs: https://t.co/C0gTKTc04J model: https://t.co/ean1UgetSH repo:… https://t.co/gJIon3FH07
Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs abs: https://t.co/LtM4Xq1Jdy project page: https://t.co/KBx04WuoNQ code: https://t.co/PVpxWPnw4h models/data/benchmark: https://t.co/WaEtWmpsrS Introduces: - a more vision-centric benchmark, CV-Bench - a… https://t.co/evyFi1Do8N