Graph transformer networks allow multimodule document recognition systems to be trained globally with gradient methods to minimize overall performance.

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Our reading — they may agree, disagree or merely touch the same thing. Closest first: a shared subject counts for most, then how near the wording is.

• Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. AVAshish Vaswani12 Jun 2017similar wording
• A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. AVAshish Vaswani12 Jun 2017similar wording
• Work on large language models is not progress toward artificial general intelligence, because the models do not understand what they read. AGAlexey Guzey9 Aug 2024similar wording
• With suitable architecture, gradient-based learning can form decision surfaces that classify high-dimensional patterns such as handwritten characters with minimal preprocessing. YBYoshua Bengio1 Jan 1998similar wording
• Residual networks are easier to optimize than plain ones and keep gaining accuracy as depth increases. KHKaiming He10 Dec 2015similar wording

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