AI Models Show Different Learning Paths To Abstract Reasoning
AI models show different paths to abstract reasoning: Function vs Direct Prediction. Two approaches explored: inferring latent functions or directly predicting new test outputs using neural networks on ARC dataset.
This is a Plain English Papers summary of a research paper called AI Models Show Different Learning Paths to Abstract Reasoning: Function vs Direct Prediction. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter. Overview The paper explores whether it's better to infer a latent function that explains a few examples, or to directly predict new test outputs using a neural network. The experiments are conducted on the ARC dataset, which contains abstract reasoning tasks. The models are trained on synthetic data generated by prompting large language...