Explore how large language models can adapt to new tasks without parameter updates through in-context learning, challenging traditional machine learning paradigms and enabling powerful zero-shot capabilities.
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Sparse Attention in Transformers: Scaling Sequence Modeling to New Heights
Explore how sparse attention mechanisms overcome the quadratic complexity limitation of transformers, enabling efficient processing of extremely long sequences for advanced AI applications.