willccbb

version = 1
revision = 2
requires-python = ">=3.11, <3.13"
resolution-markers = [
    "python_full_version >= '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux'",
    "python_full_version >= '3.12' and platform_machine != 'aarch64' and sys_platform == 'linux'",
    "python_full_version >= '3.12' and sys_platform == 'darwin'",
    "python_full_version >= '3.12' and sys_platform != 'darwin' and sys_platform != 'linux'",
    "python_full_version < '3.12' and platform_machine == 'aarch64' and sys_platform == 'linux'",
    "python_full_version < '3.12' and platform_machine != 'aarch64' and sys_platform == 'linux'",

willccbb

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "click",
#     "mistralai",
#     "markdown",
#     "requests",
#     "beautifulsoup4",
# ]
# ///

willccbb

Approaches to Solving the ARC-AGI Challenge: A Comprehensive Analysis

Table of Contents

1. Introduction
2. Understanding the ARC-AGI Challenge
3. Historical Progress on ARC-AGI
4. Current Approaches
   • Program Synthesis Approaches
   • Large Language Model Approaches

• Hybrid Approaches

willccbb

# train_grpo.py
#
# See https://github.com/willccbb/verifiers for ongoing developments
#
"""
citation:

@misc{brown2025grpodemo,
  title={Granular Format Rewards for Eliciting Mathematical Reasoning Capabilities in Small Language Models},
  author={Brown, William},