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SciReasoner achieves a remarkable 31% improvement in Cellular Component annotation for low-homology proteins, showcasing the power of structural reasoning in AI.
Achieving trillion-parameter performance with just 35 billion parameters by scaling agent horizons reveals a new frontier in model efficiency.
LLMs can slash the search space for physical laws by 100,000x, yielding simpler and more accurate formulas for materials properties.
Forget RLHF, self-play, or chain-of-thought: geometric consensus with sparse supervision unlocks scientific reasoning in LLMs.
