Results for "data → model"

Extracting system prompts or hidden instructions.

Optimizes future actions using a model of dynamics.

Mathematical representation of friction forces.

Internal representation of the agent itself.

Methods that learn training procedures or initializations so models can adapt quickly to new tasks with little data.

A parameterized function composed of interconnected units organized in layers with nonlinear activations.

Ability to replicate results given same code/data; harder in distributed training and nondeterministic ops.

Autoencoder using probabilistic latent variables and KL regularization.

A theoretical framework analyzing what classes of functions can be learned, how efficiently, and with what guarantees.

Agents communicate via shared state.

Chooses which experts process each token.

Differences between simulated and real physics.

Models effects of interventions (do(X=x)).

Differences between training and deployed patient populations.

Configuration choices not learned directly (or not typically learned) that govern training or architecture.

Attention where queries/keys/values come from the same sequence, enabling token-to-token interactions.

Crafting prompts to elicit desired behavior, often using role, structure, constraints, and examples.

Constraining model outputs into a schema used to call external APIs/tools safely and deterministically.

A model is PAC-learnable if it can, with high probability, learn an approximately correct hypothesis from finite samples.

A measure of a model class’s expressive capacity based on its ability to shatter datasets.

Measures a model’s ability to fit random noise; used to bound generalization error.

Encodes token position explicitly, often via sinusoids.

Models time evolution via hidden states.

Using limited human feedback to guide large models.

Requirement to provide explanations.

Maximum system processing rate.

Acting to minimize surprise or free energy.

Predicting disease progression or survival.

Fabrication of cases or statutes by LLMs.

Quantifying financial risk.