GSM8K Dataset Papers With Code

GSM8K is a dataset of 8.5K high quality linguistically diverse grade school math word problems created by human problem writers. The dataset is segmented into 7.5K training problems and 1K test problems. These problems take between 2 and 8 steps to solve, and solutions primarily involve performing a sequence of elementary calculations using basic arithmetic operations (+ − ×÷) to reach the final answer. A bright middle school student should be able to solve every problem. It can be used for multi-step mathematical reasoning.

PDF] Large Language Models are Better Reasoners with Self-Verification

How Surge AI Built OpenAI's GSM8K Dataset of 8,500 Math Problems

How Surge AI Built OpenAI's GSM8K Dataset of 8,500 Math Problems

2201.11903] Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions

Darren Angle on LinkedIn: 3 quick prompt engineering tips for better outputs from large language…

How Surge AI Built OpenAI's GSM8K Dataset of 8,500 Math Problems

How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition – arXiv Vanity

Papers with Code

TinyGSM: achieving >80% on GSM8k with small language models

Yicheng Zou - CatalyzeX

How Surge AI Built OpenAI's GSM8K Dataset of 8,500 Math Problems

ToRA: a tool-integrated reasoning agent for mathematical problem solving, surpassing prior open source models on 10 mathematical reasoning datasets : r/LocalLLaMA

Phi-1.5: 41.4% HumanEval in 1.3B parameters (model download link in comments) : r/LocalLLaMA