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Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 23, 2026 · Artificial Intelligence

10M‑Parameter Model Solves ARC and Sudoku – Bengio Team Bets on Multi‑Trajectory Reasoning

A 10‑million‑parameter GRAM model from Bengio, KAIST, Mila and NYU achieves 97% accuracy on Sudoku‑Extreme and competitive scores on ARC‑AGI tasks by replacing deterministic recursive updates with a probabilistic multi‑trajectory process, and extensive ablations show that both random guidance and depth‑supervised training are essential for its performance.

ARC‑AGIGRAMGenerative Recursive Reasoning
0 likes · 9 min read
10M‑Parameter Model Solves ARC and Sudoku – Bengio Team Bets on Multi‑Trajectory Reasoning
Machine Learning Algorithms & Natural Language Processing
Machine Learning Algorithms & Natural Language Processing
May 22, 2026 · Artificial Intelligence

How a 10M‑Parameter Model Beats Large Models on Sudoku and ARC with Multi‑Trajectory Reasoning

The GRAM model introduced by Yoshua Bengio’s team replaces deterministic recursive updates with probabilistic multi‑trajectory sampling, enabling a 10 M‑parameter network to achieve 97 % accuracy on Sudoku‑Extreme, 52 %/11 % on ARC‑AGI, and near‑perfect results on N‑Queens and graph‑coloring, while also supporting unconditional generation tasks.

ARC‑AGIGRAMSudoku
0 likes · 9 min read
How a 10M‑Parameter Model Beats Large Models on Sudoku and ARC with Multi‑Trajectory Reasoning
AI Engineering
AI Engineering
Feb 5, 2026 · Artificial Intelligence

Claude Opus 4.6 Launches with a Record 68% ARC‑AGI Score

Anthropic’s Claude Opus 4.6 launches with a 68% ARC‑AGI score, a 1 million‑token context window, top rankings on Terminal‑Bench 2.0, Humanity’s Last Exam, and GDPval‑AA, unchanged pricing, enhanced safety, and new API features such as adaptive thinking and context compression.

AI modelARC‑AGIAnthropic
0 likes · 5 min read
Claude Opus 4.6 Launches with a Record 68% ARC‑AGI Score