Despite a 100,000x increase in scaling since 2019, base LLMs without test-time compute continue to perform poorly on the ARC-AGI benchmark for unseen tasks. This performance gap highlights the necessity of the test-time compute paradigm to achieve human-level reasoning.
HOW THIS AFFECTS YOU
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builderIntegrate test-time compute to solve complex reasoning tasks that standard LLM calls fail.
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researcherBase model scaling alone is insufficient for mastering generalization on reasoning benchmarks.