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Unraveling Molecular Structure: A Multimodal Spectroscopic Dataset for Chemistry Marvin Alberts
Spectroscopic techniques are essential tools for determining the structure of molecules.
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Transformers Can Do Arithmetic with the Right Embeddings
We mend this problem by adding an embedding to each digit that encodes its position relative to the start of the number.
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Unraveling the Gradient Descent Dynamics of Transformers
By analyzing the loss landscape of a single Transformer layer using Softmax and Gaussian attention kernels, our work provides concrete answers to these questions.
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Unveiling Induction Heads: Provable Training Dynamics and Feature Learning in Transformers Siyu Chen Department of Statistics and Data Science, Yale University
In particular, most existing work only theoretically explains how the attention mechanism facilitates ICL under certain data models.
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