Glossary

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LIME(also: Local Interpretable Model-agnostic Explanations)

An explainable AI technique, introduced by Ribeiro et al. in 2016, that approximates any black-box model's behaviour around a single prediction by fitting a simple interpretable model (usually sparse linear regression) to perturbed versions of the input. The resulting feature…

LLM Agent(also: Generative Agent, Task-Executing Agent)

A software system built around a large language model that autonomously perceives state, plans actions, executes them against an environment (a web page, a mobile app, a shell, a UI), and reflects on outcomes to make progress toward a goal. In accessibility work, LLM agents are…

LLM Disability Bias(also: AI Ableism, Language Model Disability Bias)

Systematic prejudice against people with disabilities embedded in large language models due to biased training data and development processes that underrepresent disabled communities. Research has documented multiple forms of this bias: pretrained language models associate…

LLM Hallucination(also: AI Hallucination, Model Hallucination)

The phenomenon where large language models generate content that is factually incorrect, fabricated, or not grounded in the input provided, while presenting it with apparent confidence. In bias research, hallucinations are particularly concerning because models may invent…

LLM-Based Auto Correction(also: AI-Powered Text Correction, LLM Autocorrect)

The use of large language models to automatically detect and correct common text errors without requiring manual user intervention. In accessibility contexts, LLM-based auto correction can reduce the editing burden for users with disabilities by fixing predictable errors…

LLM-as-Judge(also: LLM as a Judge, Model-as-Judge)

An evaluation methodology in which a large language model is prompted to assess the quality of some artifact — generated text, code, a UI, or a response from another model — according to a structured rubric. LLM-as-judge is attractive because it scales automated evaluation to…

LSTM(also: Long Short-Term Memory, LSTM Network)

A type of recurrent neural network architecture designed to learn long-term dependencies in sequential data by using special gating mechanisms that control the flow of information through the network. LSTMs are particularly effective for processing time-series data such as…

Language Model(also: Statistical Language Model, LM)

A computational model that assigns probabilities to sequences of words, enabling prediction of likely next words or sentences in text. In assistive technology, language models power word and sentence prediction systems by learning patterns from training corpora. Modern AAC…

Language Understanding Intelligent Service(also: LUIS, Azure LUIS)

A cloud-based Microsoft Azure service that applies machine learning to natural language text to predict meaning and extract relevant information. LUIS identifies user intents (what they want to do) and entities (key information in their utterance). In accessibility applications,…

Large Language Model(also: LLM)

A type of artificial intelligence model trained on vast amounts of text data to understand and generate human language. Large language models like GPT-4, Claude, and Gemini power many generative AI applications. In accessibility contexts, LLMs enable natural language interfaces…

Large Vision Model(also: LVM)

A large vision model is a foundation model trained on very large image (and often video) datasets to produce general-purpose visual representations - capable of object detection, segmentation, captioning, or feature extraction without task-specific retraining. Examples include…

LoRA(also: Low-Rank Adaptation)

A parameter-efficient fine-tuning technique, introduced by Hu et al. in 2022, in which a large pretrained neural network is specialised by training only a pair of small low-rank matrices that modify specific weight projections, while the original weights remain frozen. LoRA…

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