LLM Monitoring is the process of continuously tracking the performance, behavior, and outputs of Large Language Models (LLMs) during real-world deployment. This practice ensures that the models maintain reliability, relevance, and alignment with user expectations, while also detecting and addressing...

LLM Evaluation refers to the systematic assessment of Large Language Models (LLMs) to measure their performance, reliability, and alignment with desired objectives. This process employs a variety of metrics and methodologies to evaluate the quality of outputs, identify limitations, and...

An LLM Agent is an AI application that leverages the capabilities of a Large Language Model (LLM) to perform specific tasks autonomously. By combining the generative power of LLMs with logic, memory, and external data sources, LLM agents can act...

Large Language Model (LLM) is a type of AI model designed to process, understand, and generate human-like text. LLMs are trained on vast amounts of text data and use transformer-based architectures to excel in a wide range of natural language...

Latent space refers to the abstract, multidimensional space where data is represented in a compressed or encoded form. It is created by machine learning models, such as neural networks or autoencoders, to capture the most essential features of data, removing...

LangChain is a framework designed for building applications powered by Large Language Models (LLMs) that integrate external data sources, memory, and complex workflows. It allows developers to create sophisticated AI applications by chaining multiple LLM queries together and incorporating retrieval-based...

KorNAT (Korean National Alignment Test) is a benchmark dataset developed to assess the alignment of Large Language Models (LLMs) with South Korean social values and common knowledge. It evaluates models across two primary dimensions: Social Value Alignment: Measures how well...

A knowledge graph is a structured representation of information where entities (nodes) are connected by relationships (edges) to form a graph. It organizes and links data in a way that allows machines to understand, retrieve, and infer new information efficiently,...

Keras is an open-source deep learning framework designed to simplify the creation and deployment of neural networks. It provides an intuitive, user-friendly interface for building and training models while offering compatibility with powerful backends like TensorFlow, Theano, and Microsoft Cognitive...

Instruction Tuning is the process of refining large language models (LLMs) so that they better follow user-provided instructions or prompts. Rather than simply predicting the next word based on statistical patterns, instruction-tuned models are trained on curated datasets of prompts...