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Find an AI concept.
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AI for Science
AI-assisted scientific prediction and candidate selection, with attention to experimental validation, data leakage and the scope of automated research.
BERT
Bidirectional Encoder Representations from Transformers, an encoder-based language representation model.
Benchmark Data Contamination
The presence of evaluation examples or closely related material in training data, potentially inflating benchmark results.
Data Provenance
Information about where data came from, how it was collected, and how it changed before use.
Datasheets for Datasets
A documentation framework for describing how datasets were created, composed, maintained, and intended to be used.
Fine-tuning
Additional training that adapts a pre-trained model to a narrower task, domain, or behavior.
Foundation Model
A broadly trained model that can be adapted to many downstream tasks and applications.
HELM
Holistic Evaluation of Language Models, a framework for evaluating models across scenarios and metrics.
Hallucination in AI
A generated statement that is unsupported, fabricated, or inconsistent with the available evidence or context.
Knowledge Distillation
A training method in which a smaller student model learns from the outputs or representations of a larger teacher model.
MMLU
Massive Multitask Language Understanding, a benchmark covering many academic and professional subject areas.
Model Card
A structured document that describes a model's intended use, evaluation, limitations, and other important context.
Retrieval-Augmented Generation (RAG)
A method that retrieves external information and supplies it to a generative model as context.