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LLMs for math problems: overcoming the challenges

  Machine learning

LLMs for math problems: overcoming the challenges While large language models excel in many NLP tasks, they often struggle with even trivial math problems. LMs are notoriously bad at working with numbers and often fail due to flawed reasoning. The first issue can be solved entirely by teaching models to use mathematical tools, but reliable reasoning remains a formidable challenge. We will demonstrate how to improve reasoning capabilities using preference optimization, a recent technique for aligning LMs with feedback. This method teaches the model to prefer generating correct solutions ove...