Query‑Key‑Value (QKV) Attention
Transformer mechanism computing attention weights from queries and keys to mix values across tokens.
Transformer mechanism computing attention weights from queries and keys to mix values across tokens.
Mapping from state‑action pairs to expected returns, often approximated with neural networks.
Expected return of taking an action in a state under a policy, central to Q‑learning and DQN.
Model‑free reinforcement learning algorithm that learns action‑value functions to maximize cumulative reward.
Parameter‑efficient fine tuning approach that combines low‑rank adaptation with quantized base weights to cut VRAM use.
Training procedure that simulates low‑precision arithmetic during training to preserve accuracy after quantization.
Compressing model weights and activations to lower precision, for example 8‑bit or 4‑bit, to reduce memory and speed up inference.
Voting mechanism where the cost of additional votes grows quadratically, balancing intensity and fairness.
Public goods funding mechanism where many small donations receive higher matching than a few large ones, encouraging broad support.
Social engineering attack where an adversary tricks a user into revealing secrets or signing malicious transactions.