AMC

The 'AMC' dataset/benchmark contains a collection of questions designed to evaluate the reasoning capabilities of large language models by assessing their performance on problem-equivalent rephrasings.

Papers using AMC (7)

Distribution-Aware Reward Estimation for Test-Time Reinforcement Learning2026Transformation-Augmented GRPO for Enhancing Exploration in Reasoning of Large Language Models2026SEED-GRPO: Semantic Entropy Enhanced GRPO for Uncertainty-Aware Policy Optimization2025LIMOPro: Reasoning Refinement for Efficient and Effective Test-time Scaling2025Inpainting-Guided Policy Optimization for Diffusion Large Language Models2025Efficient Reinforcement Finetuning via Adaptive Curriculum Learning2025Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning2025