Glossary
Searchable terminology from accessibility, web standards, and related fields.
79 results found in Artificial Intelligence.
- LLM Hallucination (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 resear…
- LLM-as-Judge (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 …
- LSTM (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.…
- Large Language Model (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 ap…
- Large Vision Model (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, caption…
- LoRA (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 s…
- Markov Decision Process (MDP)
- A mathematical framework for modelling decision-making in situations where outcomes are partly random and partly under the control of a decision-maker. In accessibility and assistive technology, Marko…
- Meta-learning (Learning to Learn)
- A branch of machine learning where models are trained to learn new tasks from very few examples by leveraging knowledge gained from previous tasks. In accessibility applications, meta-learning enables…
- Minimum Viable Description (MVD)
- Minimum viable description (MVD) is an emerging framework for audio description that establishes the foundational level of visual information needed to provide equal access to video content without in…
- Mixture of Experts (MoE)
- Mixture of experts is a neural network architecture that routes each input through a small subset of specialist subnetworks ('experts') rather than activating the whole model. A gating network decides…
- Multimodal AI (Multimodal Generative AI)
- Artificial intelligence systems capable of processing and generating content across multiple modalities such as text, images, audio, and video. In accessibility contexts, multimodal AI is significant …
- Natural Language Processing (NLP, Computational Linguistics)
- A branch of artificial intelligence that enables computers to understand, interpret, and generate human language. In accessibility, NLP powers voice-based assistive technologies, automatic captioning,…
- Neural Radiance Field (NeRF)
- An implicit neural representation of a 3D scene, introduced by Mildenhall et al. in 2020, in which a small neural network is trained to map any 3D coordinate and viewing direction to a colour and dens…
- Parameter-Efficient Fine-Tuning (PEFT, Lightweight Fine-Tuning)
- Parameter-efficient fine-tuning is a family of techniques (LoRA, adapters, prefix tuning, prompt tuning) that adapt a large pretrained model to a new task or domain by updating only a small fraction o…
- Perceptual Gap
- A design failure identified by Choudhury (2026) in which an AI system's explanation is delivered through exactly the sensory channel that its user cannot access. For example, a Grad-CAM heat map overl…
- Recurrent Neural Network (RNN)
- A recurrent neural network (RNN) is a type of artificial neural network designed to process sequential data by maintaining an internal state (memory) that captures information from previous inputs in …
- Reinforcement Learning from Human Feedback (RLHF)
- A machine learning technique used to fine-tune large language models by incorporating human judgments about response quality. Human annotators rank or rate model outputs, and this feedback trains a re…
- Relevance Scoring (Task Relevance Score, Content Relevance Rating)
- The assignment of numerical scores to web page elements indicating how relevant they are to a user's specified task or goal. In systems like Task Mode, relevance scores typically range from 0 (complet…
- SHAP (SHapley Additive exPlanations)
- A unified framework for feature-importance explanations of machine-learning models, introduced by Lundberg and Lee in 2017, grounded in Shapley values from cooperative game theory. For any model and i…
- Scene Segmentation (Scene Detection, Shot Boundary Detection)
- Scene segmentation is the process of automatically dividing a video into discrete scenes or segments based on visual changes such as cuts, transitions, or the appearance of new elements in the frame. …