Results for "rule-based"

Strategy mapping states to actions.

Extending agents with long-term memory stores.

Expected return of taking action in a state.

Coordination arising without explicit programming.

Optimizing policies directly via gradient ascent on expected reward.

Categorizing AI applications by impact and regulatory risk.

Learning from data generated by a different policy.

Extracting system prompts or hidden instructions.

Models trained to decide when to call tools.

Neural networks that operate on graph-structured data by propagating information along edges.

GNN framework where nodes iteratively exchange and aggregate messages from neighbors.

Diffusion model trained to remove noise step by step.

Extension of convolution to graph domains using adjacency structure.

Assigning category labels to images.

GNN using attention to weight neighbor contributions dynamically.

Pixel-level separation of individual object instances.

Joint vision-language model aligning images and text.

Pixel motion estimation between frames.

Predicting future values from past observations.

Repeating temporal patterns.

Optimal estimator for linear dynamic systems.

Maintaining two environments for instant rollback.

Using production outcomes to improve models.

System that independently pursues goals over time.

Interleaving reasoning and tool use.

Agent reasoning about future outcomes.

Sum of independent variables converges to normal distribution.

Updated belief after observing data.

Belief before observing data.

Optimization under uncertainty.