InternLM-XComposer-2.5 (IXC-2.5): A Versatile Large-Vision Language Model that Supports Long-Contextual Input and Output
What are Large Vision Language Models (LVLMs)?
Large Vision Language Models (LVLMs) are advanced AI models that integrate visual and textual information processing capabilities5. They aim to bridge the gap between open-source and closed-source models, offering versatility and performance in vision-language comprehension and composition tasks. LVLMs have shown promise in areas such as image analysis, video understanding, and text-image conversations, with continuous efforts being made to enhance their capabilities and applicability in real-world scenarios.
What challenges do open-source LVLMs face?
Open-source LVLMs face challenges in matching the versatility of proprietary models like GPT-4, Gemini Pro, and Claude 3. The primary obstacles include limited diversity in training data and difficulties in handling long-context input and output. Researchers are striving to enhance open-source LVLMs' ability to perform a wide range of vision-language comprehension and composition tasks, bridging the gap between open-source and closed-source leading paradigms in terms of versatility and performance across various benchmarks.