ChatRex: A Multimodal Large Language Model (MLLM) with a Decoupled Perception Design

Understanding Multimodal Large Language Models (MLLMs) Multimodal Large Language Models (MLLMs) are advanced AI systems that can process both text and images. However, they face challenges with specific tasks like object detection, which is crucial for technologies such as self-driving cars and robots. For example, the current model Qwen2-VL can only detect 43.9% of objects correctly, mainly due to conflicting tasks and insufficient training data. Challenges in Current Models Current approaches to improve object detection in MLLMs typically use bounding box coordinates. While these work for understanding text, they often result in mistakes during object detection. Existing models can change detection methods but lack reliability for real-world use. The training data also fails to properly support both perception (seeing) and understanding (comprehending) tasks. Introducing ChatRex To overcome these challenges, researchers from the International Digital Economy Academy (IDEA) developed ChatRex. This advanced MLLM separates the tasks of seeing and understanding. It utilizes a new retrieval-based framework for object detection, which effectively retrieves bounding box indices rather than predicting coordinates, leading to fewer errors and improved accuracy. Key Features of ChatRex - **Universal Proposal Network (UPN):** Produces clear bounding box proposals, helping clarify object representation. - **Dual-Vision Encoder:** Combines high and low-resolution images to improve object detection accuracy. - **Rexverse-2M Dataset:** Contains over two million annotated images for balanced training in both perception and understanding. Performance and Applications ChatRex shows better performance in object detection, achieving higher accuracy and precision than existing models. It successfully connects descriptive text to objects, generates meaningful captions, and manages complex text and visual interactions effectively. Why Choose ChatRex? ChatRex uniquely addresses the long-standing issues between perception and understanding tasks. Its innovative design and comprehensive training data establish new standards for MLLMs. This integration enhances object detection and contextual understanding, unlocking new potential for AI in dynamic environments. Transform Your Business with AI Stay competitive with ChatRex, the advanced MLLM with a smart perception design. Here’s how AI can improve your processes: 1. **Identify Automation Opportunities:** Discover key interactions that can benefit from AI. 2. **Define KPIs:** Establish measurable impacts for your AI projects. 3. **Select an AI Solution:** Choose tools that match your needs and offer customization. 4. **Implement Gradually:** Start with a pilot project, gather data, and expand AI usage wisely. For advice on AI KPI management, reach out to us. For ongoing insights into effective AI use, follow us on social media. Enhance Your Sales and Customer Engagement Learn how AI can improve your sales processes and enhance customer interactions. Explore more solutions on our website.