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AgentFold not only outperforms traditional model improvement methods but also uncovers essential design patterns that could redefine protein folding strategies.
Benchmark gains in LLMs can be misleading, as they may reflect improved reachability rather than true capability expansion, with significant implications for performance evaluation.
ABOPD achieves a remarkable 0.42 Å reduction in RMSD for antibody CDR design, setting a new standard for structural fidelity in protein generation.
Current AI agents struggle to reliably rediscover scientific knowledge, with top performers averaging only 21.5 out of a possible score, revealing critical gaps in their research capabilities.
Skip the expensive proxy model training: this training-free method boosts VLLM performance by up to 4.8% using only 10-15% of the data, simply by measuring how much the question *changes* the model's view of the answer.
Imagine AI scientists that not only reason but also autonomously conduct experiments in the real world – that's the promise of Intelligent Science Laboratories.
