ATLAS traces RLVR data to 20 atomic sources, most datasets are variants, and DAPO++ curated with SCA improves RLVR performance while Q predicts training effectiveness.
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A structured survey of LLM mathematical reasoning that unifies dataset taxonomies, reviews architectures and training strategies, and highlights the gap between answer accuracy and process-level verification.
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RLVR Datasets and Where to Find Them: Tracing Data Lineage for Better Training Data
ATLAS traces RLVR data to 20 atomic sources, most datasets are variants, and DAPO++ curated with SCA improves RLVR performance while Q predicts training effectiveness.
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Mathematical Reasoning in Large Language Models: Benchmarks, Architectures, Evaluation, and Open Challenges
A structured survey of LLM mathematical reasoning that unifies dataset taxonomies, reviews architectures and training strategies, and highlights the gap between answer accuracy and process-level verification.