SHYRS: A proof of concept for specifying how humans solve ARC-AGI-2 puzzles
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Updated
Jan 5, 2026
SHYRS: A proof of concept for specifying how humans solve ARC-AGI-2 puzzles
Abstract Port Graphs (APG) is a framework for representing programs as graphs for program synthesis. This repo includes a domain specific representation for ARC-AGI
Synalinks ARCAGI2 public benchmark
PUMA – Program Understanding & Meta-learning Architecture Neuroscience-inspired meta-learning system for solving ARC-AGI-2 tasks through RFT-(Relational Frame Theory), symbolic reasoning, neural guidance, and test-time adaptation. #ARC2025
Official package for "A Neural Affinity Framework for Abstract Reasoning." Includes the validated 9-category ARC taxonomy, pre-computed fine-tuning results, and scripts to verify the Compositional Gap.
Pure-Python baseline solver for Kaggle ARC Prize 2025 on ARC-AGI-2
A very simplistic approach to solving ARC-AGI-2. Designed to be a neural network built off of primitive functions with special tweaks. This model strives to be as simple and quick as possible as well.
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