Large language models (LLMs)
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Amazon and UT Austin announce inaugural award and fellowship recipients
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The UT Austin-Amazon Science Hub has announced the inaugural winners of two gift project awards and a doctoral graduate fellowship. The awards recognize ...

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A quick guide to Amazon’s 40+ papers at EMNLP 2023
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Natural-language understanding (NLU) has long been a central focus of the papers that Amazon researchers publish at the Conference on Empirical Methods in ...

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Amazon and MIT announce Science Hub 2023 gift project awards and fellowships
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Amazon and MIT have named the recipients of the 2023 gift project and fellowship awards granted as part of the Science Hub.The Science Hub — administered at ...

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New tool, dataset help detect hallucinations in large language models
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For all their remarkable abilities, large language models (LLMs) have an Achilles heel, which is their tendency to hallucinate, or make assertions that ...

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Vision-language models that can handle multi-image inputs
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Vision-language models, which map images and text to a common representational space, have demonstrated remarkable performance on a wide range of multimodal ...

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Amazon and IIT Bombay announce inaugural award recipients
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Amazon and IIT Bombay (IIT-B) today announced the inaugural award recipients of the Amazon IIT–Bombay AI-ML Initiative. The awards recognize researchers ...

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Do large language models understand the world?
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For centuries, theories of meaning have been of interest almost exclusively to philosophers, debated in seminar rooms and at conferences for small specialty ...

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Building commonsense knowledge graphs to aid product recommendation
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At the Amazon Store, we strive to deliver the product recommendations most relevant to customers’ queries. Often, that can require commonsense reasoning. If ...

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Updating large language models by directly editing network layers
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One of the great attractions of large language models (LLMs) is that they encode information about the real world. But the world is constantly changing, and ...

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