The Sequence Scope: OpenAI New NLP Challenge: Mathematical Reasoning
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📝 Editorial: OpenAI New NLP Challenge: Mathematical Reasoning
Mathematical reasoning has long been one of the mystical challenges for ML models. In recent years, we have seen tremendous advances in natural language processing(NLP) with methods such as transformers powering models like GPT-3 that can solve many complex language tasks. However, even those models struggle when presented with multi-step mathematical reasoning problems. Take a simple word math problem such as the following :
“Tim grows 5 trees. Each year he collects 6 lemons from each tree. How many lemons does he get in a decade?”
From an ML perspective, creating a model that solves these types of problems presents some fundamental challenges. In addition to the sophisticated interpretability required in math reasoning problems, they are very sensitive to cascading errors. Mathematical reasoning models need to be able to correct mistakes accordingly and concatenate a complex sequence of steps. Not surprisingly, many experts believe that mathematical reasoning problems are a way to expose the limitations of NLP models.
Despite the challenges, the AI community has been steadily making progress towards creating ML models specialized in multi-step mathematical reasoning. A few days ago, OpenAI published a paper outlining some methods to tackle word math problems. As part of their research, OpenAI also open-sourced GSM8K, a dataset of 8.5K high-quality problems at the grade school math level with varying levels of linguistic diversity. The research from OpenAI favors a dual method in which a model generates many candidate solutions, and a verifier model evaluates the correctness of…