Print Join the Discussion View in the ACM Digital Library The mathematical reasoning performed by LLMs is fundamentally different from the rule-based symbolic methods in traditional formal reasoning.
Engineers at the University of California San Diego have developed a new way to train artificial intelligence systems to ...
Do you stare at a math word problem and feel completely stuck? You're not alone. These problems mix reading comprehension ...
Chain-of-Thought (CoT) prompting has enhanced the performance of Large Language Models (LLMs) across various reasoning tasks.
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Abstract: Though quite challenging, training a deep neural network for automatically solving Math Word Problems (MWPs) has increasingly attracted attention due to its significance in investigating how ...
Abstract: In expensive multitask optimization problems (ExMTOPs), multiple complex tasks must be optimized simultaneously under limited computational budgets. Existing approaches, often based on ...
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