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#algorithmic-reasoning

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papersTODAY 04:00 UTC

Graph Neural Algorithmic Reasoning Reframed as a Reinforcement Learning Problem

A revised arXiv paper argues that neural algorithmic reasoning, which typically trains networks to imitate classic algorithms via supervised learning, is limited by its reliance on post-processing to produce valid outputs. The authors propose reformulating the task as a reinforcement learning problem, aiming to let models build correct solutions directly rather than repairing them afterward. The work appears in the cs.LG and cs.AI listings as a replacement submission.

graph-neural-networks/reinforcement-learning/algorithmic-reasoning/arxiv