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GeniX - When Agent Becomes the Scientist – Building Closed-Loop System from Hypothesis to Verification

[ Paper πŸ““ ] [ Website 🏠 ] [ GeniX Examples πŸ€— ]

From One Idea to Autonomous Experimentation

πŸ”₯ News

  • 2025.06.02:   NovelSeek will be renamed GeniX in two days (meaning Genius + X, representing infinite possibilities). This change embodies our hopeful vision for autonomous scientific research framework, and we hope it will empower all researchers to achieve great scientific discoveries.

πŸ“– Overview

GeniX

GeniX 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

GeniX 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.

GeniX is a unified, closed-loop multi-agent system designed to automate and accelerate innovative research across scientific domains. Through intelligent agent collaboration, GeniX enables end-to-end automation from idea generation and methodology construction to experimental execution, dramatically enhancing research efficiency and creativity.

πŸ’‘ Self-Evolving Idea Generation with Human-Interactive Feedback

  • Autonomous generation, selection, and evolution of innovative research ideas through multi-agent collaboration
  • Supports interactive human feedback, enabling continuous refinement of ideas with expert insights
  • Dynamically integrates literature, code, and domain knowledge to inspire diverse innovation pathways

πŸ—οΈ Idea-to-Methodology Construction

  • Systematically transforms creative ideas into actionable and verifiable research methodologies
  • Integrates baseline code, literature, and expert knowledge to automatically generate comprehensive methodological frameworks
  • Supports iterative refinement and traceability of research methods

πŸ› οΈ Evolutionary Experimental Planning and Execution

  • Automates complex experimental workflow planning, code implementation, and debugging
  • Employs exception-guided intelligent debugging to automatically identify and resolve code issues
  • Enables adaptive evolution and continuous optimization of experimental plans

πŸ€– Multi-Agent Orchestration

  • Coordinates specialized agents such as Survey, Coding, Idea Innovation, and Assessment Agents and so on
  • Manages data flow, task scheduling, and human interaction points for efficient and coherent research processes
  • Supports extensibility and compatibility with diverse scientific tasks

GeniX delivers an "end-to-end algorithmic innovation", empowering AI+X researchers to rapidly complete the full research loopβ€”from idea to methodology to experimental validationβ€”accelerating scientific discovery and breakthroughs.

πŸ”¬ Supported Research Tasks

  • Suzuki Yield Prediction
  • Molecular Dynamics Simulation
  • Enhancer Activity Prediction
  • Transcription Prediction for Perturbation Respons
  • Power Flow Estimation
  • Time Series Forecasting
  • Semantic Segmentation
  • Image Classification
  • Sentiment Analysis
  • Point Cloud Classification
  • Point Cloud Object Detection
  • VLM & LLM Fine-tuning
  • ......

πŸš€ Performance

By leveraging multi-source knowledge injection, GeniX 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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