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README.md

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 ## 📖 Overview
 
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 InternAgent can support **12** types of scientific research tasks ranging from the AI field to the science field, including reaction yield prediction, molecular dynamics, power flow estimation, time series forecasting, transcription prediction, enhancer activity prediction, sentiment classification, 2D image classification, 3D point classification, 2D semantic segmentation, 3D autonomous driving, large vision-language model fine-tuning.
 
 ## 🌟 Core Features
 
-![Framework](https://github.com/Alpha-Innovator/InternAgent/blob/main/images/internagent_framework.png)
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 InternAgent covers three main capabilities: (1) **Self-evolving idea generation with human-interactive feedback**, (2) **Idea-to-methodology construction**, and (3) **Evolutionary experimental planning and execution**. 
 
 It is a unified, closed-loop multi-agent system designed to automate and accelerate innovative research across scientific domains. Through intelligent agent collaboration, InternAgent enables **end-to-end automation** from idea generation and methodology construction to experimental execution, dramatically enhancing research efficiency and creativity.
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 ## 🚀 Performance
 
 By leveraging multi-source knowledge injection, InternAgent intelligently generates and verifies research ideas across multiple domains. Our system has significantly improved research efficiency in Suzuki Yield Prediction, Enhancer Activity Prediction, Transcription Prediction for Perturbation Respons, and so on.
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