Overview
This hub organizes AI research three ways: by the company or lab behind the work, by research topic, and by academic venue. Rather than a flat list, each path is built to help you find genuinely relevant material quickly — whether you're tracking a specific lab's output, researching a topic like RAG or reasoning models, or looking for what a specific conference has historically covered.
Browse by Company
OpenAI
Browse →Anthropic
Browse →Meta
Browse →Microsoft
Browse →Google DeepMind
Browse →xAI
Browse →Mistral AI
Browse →Browse by Topic
Large Language Models
Browse →Multimodal AI
Browse →Reasoning Models
Browse →AI Agents
Browse →Retrieval-Augmented Generation
Browse →Vector Databases
Browse →Fine-Tuning
Browse →Prompt Engineering
Browse →Browse by Venue
See our Conferences hub for major AI research venues including NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, and AAAI, plus arXiv as the field's primary preprint server.
Reading Papers Effectively
You don't need a deep technical background to get real value from a paper — the abstract, introduction, and conclusion are usually written to be broadly understandable, even when the methods section is dense. Check whether a result has been independently replicated, whether it's evaluated on a genuinely new problem versus one the field has already saturated, and whether the paper's own limitations section is honest about what it doesn't show.
Related Pages
Frequently Asked
Does LLMWIKI host the actual PDF of these papers?
No, this hub organizes and summarizes publicly available research; follow links to the primary source (the lab's site or the venue's proceedings) to read the full paper.
How current is this hub kept?
Research output moves quickly; see our Latest and Trending pages for a more time-sensitive view, though all research content should be verified against primary sources for anything current.
Can I suggest a paper or topic to add?
Yes, see our Contribute page for how to suggest additions.
Where do I start if I'm new to reading AI research?
See our Reading AI Research Papers guide for a practical starting framework.