Continual-ARC benchmark: leading agents fail to learn from experience, a fine-tuned 9B model does better
SimplyAnnisa · x · 2026-11-12
Unify AI launched Continual-ARC, a new benchmark for continual learning. Results show OpenClaw, Hermes Agent and Prime Agent don't meaningfully learn from experience — none memorized anything of value or generalized to new tasks — while training a small 9B model's weights achieved both. Commenters note that an AI needing fewer reminders and understanding you better over time is the progress that matters.
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