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Although Large Language Models (LLMs) achieve remarkable performance across various tasks, they often struggle with complex reasoning tasks, such as answering mathematical questions.
The HARPY speech recognition system
Bruce T. Lowerre · 1976
Earlier work this paper cites.
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