Results for "sensitivity to data"

Allows model to attend to information from different subspaces simultaneously.

Encodes token position explicitly, often via sinusoids.

Logged record of model inputs, outputs, and decisions.

Models trained to decide when to call tools.

Graphs containing multiple node or edge types with different semantics.

Compromising AI systems via libraries, models, or datasets.

Controls amount of noise added at each diffusion step.

Extension of convolution to graph domains using adjacency structure.

Combining signals from multiple modalities.

Simultaneous Localization and Mapping for robotics.

Predicting future values from past observations.

Models time evolution via hidden states.

Monte Carlo method for state estimation.

Repeating temporal patterns.

Low-latency prediction per request.

Using production outcomes to improve models.

Increasing model capacity via compute.

Models accessible only via service APIs.

Set of vectors closed under addition and scalar multiplication.

Vector whose direction remains unchanged under linear transformation.

Measures similarity and projection between vectors.

Describes likelihoods of random variable outcomes.

Measure of spread around the mean.

Normalized covariance.

Eliminating variables by integrating over them.

Optimization under uncertainty.

Using limited human feedback to guide large models.

Model behaves well during training but not deployment.

Multiple examples included in prompt.

Prompt augmented with retrieved documents.