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Large language model

A large language model (LLM) is an AI model (typically a neural network) trained on a vast amount of text for natural language processing tasks, especially language generation. LLMs can typically generate, summarize, translate, and analyze text in many contexts. They are the basis for many modern chatbots, such as ChatGPT, Claude, Gemini, Grok, and DeepSeek.

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Overview

History

Dataset preprocessing

Training

Architecture

Extensibility

Forms of input and output

Properties

Interpretation

Evaluation

Limitations and challenges

Safety

Societal concerns

Advanced semantic analysis

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Map overview Semantic statistics

Large language model

Nodes224
Edges223
Triples131
Avg. degree1.99
Density0.008929
Components1

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Large language model

Top relations

related to Further reading · 40
Large language model → AI Index Report, An Introduction, Artificial Intelligence Index, Baby, Chaoyou, Computational Linguistics, Dan, Edition, Frank, Fu, ISSN, James, July, June, Jurafsky, Ke, Language Processing, Li, Martin, May
related to Safety · 16
Large language model → AI, ChatGPT, Claude, External, For, GPT-4o's, However, In, Kevin Esvelt, LLM, Pravda, Russia, Similarly, Some, The American Sunlight Project, Yongge Wang
see also · 15
Large language model → AI, AIAI, Artificial, Attribution, Computer, Field, LLM, Low-quality AI-generated, Nvidia, Open-source, Public, Software, Standardized AI, Studio, Type
related to Mechanistic interpretability · 8
Large language model → For, Fourier, Large, LLM, LLMs, Mechanistic, Similarly, The
related to Mental health · 7
Large language model → Clinical, Evaluations, In, LLMs, Research, Researchers, Sentio University
related to Cost · 6
Large language model → For, GPT-2, Megatron-Turing NLG, PaLM, Substantial, The
related to Human provenance · 5
Large language model → Brinkmann, In, It, LLMs, Nature Biomedical Engineering
related to Limitations and challenges · 1
Large language model → Despite

Important terminology Word statistics

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Important terminology

models llm llms model language training text data trained example parameters used large token input also displaystyle may fine-tuned 2023

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Hugging Faceinstance ofcommunity-driven contributions to open-weight models improve their efficiency and performance via collaborative platforms0.80text
GitHub Copilot offer LLMs specifically trainedinstance ofServices0.80text
fine-tunedinstance ofServices0.80text
or prompted for programming.In computational biologyinstance ofServices0.80text
transformer-based architecturesinstance ofServices0.80text
such as DNA LLMsinstance ofServices0.80text
have also proven useful in analyzing biological sequencesinstance ofServices0.80text
structure predictioninstance ofOn tasks0.80text
mutational outcome predictioninstance ofOn tasks0.80text
a small model using an embedding as input can approach or exceed much larger models using multiple sequence alignmentsinstance ofOn tasks0.80text
general knowledgeinstance ofTests evaluate capabilities0.80text
biasinstance ofTests evaluate capabilities0.80text

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