GSM8K Dataset Papers With Code
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Descrição
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.
Zhihong Shao on X: With self-consistency, ToRA-34B improves from 51% to 60% on the competition-level MATH dataset, and ToRA-70B scores 88.3% on GSM8k. Paper Page: Models: Github Repo
DeepMind Studies Process- vs Outcome-based Model Supervision, Significantly Reducing Reasoning Errors on Math Word Problems, by Synced, SyncedReview
Papers with Code
Paper page - Llemma: An Open Language Model For Mathematics
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
Linkpost] Solving Quantitative Reasoning Problems with Language Models — LessWrong
GitHub - reasoning-machines/pal: PaL: Program-Aided Language Models (ICML 2023)
The OIG Dataset
GitHub - openai/grade-school-math
PDF] Large Language Models are Better Reasoners with Self-Verification
Meta Open-Sources LLAMA-2, Overview of New Features, by OpenMMLab
Sparse Fine-Tuning for Accelerating Large Language Models with DeepSparse - Neural Magic
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