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ScoutML

Scout ML research papers with intelligent agents. A powerful command-line interface and Python library for discovering, analyzing, and implementing ML research.

  • 🚀 Quick Start

    Get up and running with ScoutML in minutes

    → Getting started

  • 🔍 Powerful Search

    Find papers using semantic search, methods, or datasets

    → Search commands

  • 🤖 AI Agents

    Get implementation guides, critiques, and experiment designs

    → Intelligent agents

  • 📊 Research Intelligence

    Analyze trends, reproducibility, and funding patterns

    → Insights

Features

  • 🔍 Advanced Search: Natural language queries with powerful filtering
  • 🤖 Intelligent Agents: AI-powered implementation guides and research analysis
  • 📊 Paper Comparison: Side-by-side analysis of multiple papers
  • 📝 Literature Reviews: Automated synthesis of research topics
  • 🎯 Similar Papers: Find related work based on content similarity
  • 💡 Research Insights: Trends in reproducibility, compute, and funding

Quick Examples

Command Line

# Search for recent transformer papers in computer vision
scoutml search "vision transformer" --year-min 2022 --sota-only

# Get implementation guide for a paper
scoutml agent implement 2010.11929 --framework pytorch

# Compare multiple papers
scoutml compare 1810.04805 2005.14165 1910.10683

# Generate a literature review
scoutml review "few-shot learning" --year-min 2020

Python Library

import scoutml

# Search for papers
results = scoutml.search("vision transformer", year_min=2022, sota_only=True)

# Get implementation guide
guide = scoutml.get_implementation_guide("2010.11929", framework="pytorch")

# Compare papers
comparison = scoutml.compare_papers("1810.04805", "2005.14165", "1910.10683")

# Generate literature review
review = scoutml.generate_review("few-shot learning", year_min=2020)

Why ScoutML?

ScoutML bridges the gap between discovering research papers and implementing them. Whether you're:

  • A researcher looking for related work
  • An engineer implementing state-of-the-art models
  • A student conducting literature reviews
  • A team lead evaluating technical approaches

ScoutML provides the tools you need to efficiently navigate the ML research landscape.

Getting Help