Microsoft unveils ‘LeMa’: A revolutionary AI learning method mirroring human problem solving
Researchers from Microsoft Research Asia, Peking University, and Xi’an Jiaotong University have developed a new technique to improve large language models’ (LLMs) ability to solve math problems by having them learn from their mistakes, akin to how humans learn.
The researchers have revealed a pioneering strategy, Learning from Mistakes (LeMa), which trains AI to correct its own mistakes, leading to enhanced reasoning abilities, according to a research paper published this week.
The researchers drew inspiration from human learning processes, where a student learns from their mistakes to improve future performance.
“Consider a human student who failed to solve a math problem, he will learn from what mistake he has made and how to correct it,” the authors explained. They then applied this concept to LLMs, using mistake-correction data pairs generated by GPT-4 to fine-tune them.
The researchers have revealed a pioneering strategy, Learning from Mistakes (LeMa), which trains AI to correct its own mistakes, leading to enhanced reasoning abilities, according to a research paper published this week.
The researchers drew inspiration from human learning processes, where a student learns from their mistakes to improve future performance.
“Consider a human student who failed to solve a math problem, he will learn from what mistake he has made and how to correct it,” the authors explained. They then applied this concept to LLMs, using mistake-correction data pairs generated by GPT-4 to fine-tune them.
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