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Ambrose Slone

2 accepted papers

2022

Exploring Length Generalization in Large Language Models

NeurIPS 2022accept

The ability to extrapolate from short problem instances to longer ones is an important form of out-of-distribution generalization in reasoning tasks, and is crucial when learning from datasets where longer problem instances are rare. These include theorem proving, solving quantitative mathematics pr…

Cited by 226SourcePDFScholar
2022

Solving Quantitative Reasoning Problems with Language Models

NeurIPS 2022accept

Language models have achieved remarkable performance on a wide range of tasks that require natural language understanding. Nevertheless, state-of-the-art models have generally struggled with tasks that require quantitative reasoning, such as solving mathematics, science, and engineering questions at…

Cited by 815SourcePDFScholar