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Weather prediction is undergoing an important shift, with data-driven AI models outperforming leading numerical weather prediction systems on average at a fraction of the computational cost. Yet, whether this success extends to extreme events remains contested. Earlier evaluations have exposed important shortcomings, b...
The results show that a model's inductive generalization reflects the latent organization of its training data, with implications for data curation and for predicting how far a learned fact will spread.
A unified framework to jointly analyze intrinsic and extrinsic gender bias in LLMs is proposed using identical neutral prompts, enabling direct comparison between gender-related information encoded in internal representations and bias expressed in generated outputs.
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