Grounding

Fine-tuning on (prompt, response) pairs to align a model with instruction-following behaviors.

Model trained to predict human preferences (or utility) for candidate outputs; used in RLHF-style pipelines.

Ensuring model behavior matches human goals, norms, and constraints, including reducing harmful or deceptive outputs.

Automated detection/prevention of disallowed outputs (toxicity, self-harm, illegal instruction, etc.).

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

Architecture that retrieves relevant documents (e.g., from a vector DB) and conditions generation on them to reduce h...

Retrieval based on embedding similarity rather than keyword overlap, capturing paraphrases and related concepts.

Breaking documents into pieces for retrieval; chunk size/overlap strongly affect RAG quality.