Results for "structured tool invocation"

Converting text into discrete units (tokens) for modeling; subword tokenizers balance vocabulary size and coverage.

The text (and possibly other modalities) given to an LLM to condition its output behavior.

Stepwise reasoning patterns that can improve multi-step tasks; often handled implicitly or summarized for safety/privacy.

Human or automated process of assigning targets; quality, consistency, and guidelines matter heavily.

Rules and controls around generation (filters, validators, structured outputs) to reduce unsafe or invalid behavior.

Central system to store model versions, metadata, approvals, and deployment state.

System for running consistent evaluations across tasks, versions, prompts, and model settings.

Stress-testing models for failures, vulnerabilities, policy violations, and harmful behaviors before release.

Separates planning from execution in agent architectures.

Diffusion performed in latent space for efficiency.

Central catalog of deployed and experimental models.

Decomposing goals into sub-tasks.

Extension of convolution to graph domains using adjacency structure.

Mathematical foundation for ML involving vector spaces, matrices, and linear transformations.

Breaking tasks into sub-steps.

US framework for AI risk governance.

Review process before deployment.

Process for managing AI failures.

Rules governing auctions.

Using markers to isolate context segments.