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Intern-S2-Preview-397B not only excels in multimodal scientific reasoning but also enhances biological instruction performance without altering its foundational architecture.
A unified evaluation framework that simplifies the assessment of LLM-based agents could drastically enhance reproducibility and accelerate research breakthroughs.
ToolMaze reveals that LLMs suffer a staggering 37% drop in recovery performance when faced with implicit semantic failures, highlighting a critical vulnerability in current models.
