applicable models
generative
Models that learn data distributions
14 techniques
| Goals | Models | Data Types | Description | |||
|---|---|---|---|---|---|---|
| GAN-Based Tabular Synthetic Data | Algorithmic | Architecture/neural Networks/generative/gan Architecture/neural Networks/generative/vae +3 | Tabular | GAN-based tabular synthetic data generation trains a generative model on a real table, then samples new rows from it to... | ||
| Prompt Robustness Testing | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Prompt robustness testing measures how much a language model's answers, or its performance on a task, change when the... | ||
| Causal Mediation Analysis in Language Models | Algorithmic | Architecture/neural Networks/transformer Architecture/neural Networks/transformer/llm +3 | Text | Causal mediation analysis traces which internal components of a language model carry the effect of a change in the input... | ||
| Fairness GAN | Algorithmic | Architecture/neural Networks/generative/gan Paradigm/generative +3 | Any | Fairness GAN is a pre-processing method that generates a synthetic training dataset in which decisions no longer track a... | ||
| Agent Goal Misalignment Testing | Testing | Architecture/model Agnostic Architecture/neural Networks/transformer/llm +3 | Text | Agent goal misalignment testing checks whether an AI agent takes unsanctioned means to reach a goal it has been given.... | ||
| Chain-of-Thought Faithfulness Evaluation | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Chain-of-thought faithfulness evaluation tests whether the step-by-step reasoning a language model writes out is what... | ||
| Few-Shot Fairness Evaluation | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Few-shot fairness evaluation tests whether the worked examples placed in a prompt change how fairly a language model... | ||
| Prompt Injection Testing | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Prompt injection testing checks whether an AI system can be made to follow instructions its builders did not intend. In... | ||
| Retrieval-Augmented Generation Evaluation | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | A retrieval-augmented generation (RAG) system answers a question by retrieving passages from a document collection and... | ||
| Toxicity Detection | Testing | Architecture/model Agnostic Architecture/neural Networks/transformer/llm +2 | Text | Toxicity detection scores a model's outputs with a classifier trained to recognise abusive language, such as insults,... | ||
| Canary Exposure Testing | Testing | Architecture/neural Networks Paradigm/generative +1 | Text | Canary exposure testing measures how strongly a training procedure makes a generative sequence model, such as a language... | ||
| Training Data Extraction Testing | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Training data extraction testing measures how much of its training text a generative language model reproduces word for... | ||
| Dangerous Capability Evaluation | Testing | Architecture/neural Networks/transformer/llm Paradigm/generative +1 | Text | Dangerous capability evaluation measures whether a frontier AI model can carry out tasks that could enable severe harm,... | ||
| C2PA Content Credentials | Algorithmic | Architecture/model Agnostic Paradigm/generative +1 | Image Text | C2PA Content Credentials attach a signed provenance record, called a manifest, to a media file, so that whoever receives... |
Rows per page
Page 1 of 1