GSM8K
A dataset that first showed signs of chain-of-thought reasoning capabilities in large language models.
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Videos Mentioning GSM8K
Stanford CS329A Self-Improving AI Agents | Part 1 | Course Overview
Stanford Online
A dataset that first showed signs of chain-of-thought reasoning capabilities in large language models.
Stanford CS329A Self-Improving AI Agents | Part 6 | Train Time Scaling/Scaling RL
Stanford Online
A dataset of grade-school math problems used to test the STAR approach.
Stanford CS329A Self-Improving AI Agents | Part 2 | Test-Time Compute Scaling
Stanford Online
A dataset used to illustrate the generation verification gap, showing that majority voting works better for simpler problems compared to more complex ones.
Stanford CS329A Self-Improving AI Agents | Part 5 | Planning and Multi-Step Reasoning
Stanford Online
A dataset of math problems used in the Swirl experiments to train and test multi-step reasoning and tool use capabilities.
Stanford CS329A Self-Improving AI Agents | Part 3 | Robust Verification
Stanford Online
A dataset of 8,500 grade school math problems designed to test multi-step reasoning in LLMs, introduced in the first paper.
Why The Harness Matters More Than The Model | YC Paper Club
Y Combinator
A benchmark used for evaluating the performance of AI agents, particularly in mathematical reasoning tasks.