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Kozuchi Agent achieves a remarkable 74.8% success rate in software repair tasks, setting a new standard for open-weight agents in the field.
ICBQ not only cuts perplexity in quantized models but also salvages performance where traditional methods falter, redefining efficiency in model compression.
ARC achieves a staggering 99.40% accuracy in long-context tasks by revolutionizing how AI agents manage and recall information.
