Grounding es el proceso de conectar la salida de un modelo de IA con fuentes de información confiables y verificables en el momento de la inferencia. En IA generativa, ayuda a mejorar la fiabilidad factual al aportar contexto relevante sin cambiar los pesos subyacentes del modelo. La generación aumentada por recuperación es una técnica común de grounding.
The process of basing all or part of an LLM's response on information retrieved from one or more trusted sources. For example, suppose a user prompts an LLM for today's weather forecast in Berlin. The LLM might ground the response on information it gathers from the European Centre for Medium-Range Weather Forecasts. Retrieval-augmented generation (RAG) is a common grounding technique.
The process of connecting a model's output to verifiable sources of information. Grounding helps to improve the accuracy, reliability, and usefulness of AI outputs by providing the model with access to specific data sources, and reduces the likelihood of hallucinations. A common type of grounding is retrieval-augmented generation (RAG).