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

HellaSwag or HellaBad? 36% of this popular LLM benchmark contains errors

HumanEval Dataset

AI tools to write (Julia) code (best/worse experience), e.g. ChatGPT, GPT 3.5 - Offtopic - Julia Programming Language

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

Sparse Fine-Tuning for Accelerating Large Language Models with DeepSparse - Neural Magic

Papers with Code

PDF] Solving math word problems with process- and outcome-based feedback

Meta Open-Sources LLAMA-2, Overview of New Features, by OpenMMLab

Papers Explained 80: Gemini 1.0. Gemini is a family of highly capable…, by Ritvik Rastogi, Dec, 2023

AK on X: MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning paper page: The recently released GPT-4 Code Interpreter has demonstrated remarkable proficiency in solving challenging math problems

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

Query and Response Augmentation Cannot Help Out-of-domain Math Reasoning Generalization

Sparse Fine-Tuning for Accelerating Large Language Models with DeepSparse - Neural Magic

Papers Explained 58: PaLM 2, by Ritvik Rastogi, DAIR.AI