Results for "step size"
Breaking tasks into sub-steps.
Temporary reasoning space (often hidden).
US approval process for medical AI devices.
A structured collection of examples used to train/evaluate models; quality, bias, and coverage often dominate outcomes.
Configuration choices not learned directly (or not typically learned) that govern training or architecture.
Maximum number of tokens the model can attend to in one forward pass; constrains long-document reasoning.
Expanding training data via transformations (flips, noise, paraphrases) to improve robustness.
Measures a model’s ability to fit random noise; used to bound generalization error.
Removing weights or neurons to shrink models and improve efficiency; can be structured or unstructured.
Attention mechanisms that reduce quadratic complexity.
Estimating parameters by maximizing likelihood of observed data.
Transformer applied to image patches.
Classical statistical time-series model.
Scaling law optimizing compute vs data.
Cost of model training.
Failure to detect present disease.
Measure of vector magnitude; used in regularization and optimization.
Effect of trades on prices.