Results for "grounded context"

Feature attribution method grounded in cooperative game theory for explaining predictions in tabular settings.

An RNN variant using gates to mitigate vanishing gradients and capture longer context.

Mechanism that computes context-aware mixtures of representations; scales well and captures long-range dependencies.

Predicts masked tokens in a sequence, enabling bidirectional context; often used for embeddings rather than generation.

Systematic differences in model outcomes across groups; arises from data, labels, and deployment context.

Samples from the smallest set of tokens whose probabilities sum to p, adapting set size by context.

Mechanisms for retaining context across turns/sessions: scratchpads, vector memories, structured stores.

Using markers to isolate context segments.

Maximum number of tokens the model can attend to in one forward pass; constrains long-document reasoning.

Techniques to handle longer documents without quadratic cost.