AI Papers Reading List

A comprehensive collection of foundational AI and LLM papers

Based on the AI Crash Course by Henry Shi

View Original Repository β†’

🎯 Start Here

πŸ“š Survey Papers

Comprehensive overview of large language models
2024
Survey of LLM-based agents
2023
Comprehensive guide to prompt engineering techniques
2024

πŸ—οΈ Foundational Modelling

The original transformer architecture paper
2017
Understanding how model performance scales with size
2020
Language models are few-shot learners
2020
Efficient fine-tuning technique using low-rank decomposition
2021
Chinchilla paper on optimal model and data scaling
2022
InstructGPT: RLHF for instruction following
2022
Simpler alternative to RLHF for alignment
2023
Using LLMs to evaluate other LLMs
2023
Sparse mixture of experts architecture
2024

🧠 Planning & Reasoning

General game-playing through self-play reinforcement learning
2017
Learning without knowing the rules
2019
Eliciting reasoning in large language models
2022
Combining reasoning traces with task-specific actions
2022
Deliberate problem solving with language models
2023
Advanced reasoning with graph structures
2023
Outcome vs. process supervision for reasoning
2023
Learning to improve reasoning chains
2024
Progress towards general intelligence through reasoning
2024
Incentivizing reasoning capability in LLMs
2025

πŸš€ Applications

Language models can teach themselves to use tools
2023
Multimodal large-scale language model
2023
Open source multilingual language models
2024
Long-context understanding and reasoning
2024
Cost-efficient mixture of experts model
2024
Agent-computer interface for automated software engineering
2024
Open platform for software development agents
2024

πŸ“Š Benchmarks

Diverse evaluation tasks for language models
2022
Evaluating language models on real-world software issues
2023
Crowdsourced benchmarking platform for LLMs
2024

πŸŽ₯ Videos & Lectures

3Blue1Brown - Visual mathematics and deep learning explanations
Build a Large Language Model From Scratch - Comprehensive book guide
Yannic Kilcher - Paper reviews and ML news
Noam Brown on Planning - Expert insights on AI planning
Foundations of LLMs - Comprehensive tutorial paper
Why You're Not Too Old to Get Into AI - Motivational perspective

🌐 Helpful Websites

History of Deep Learning - Timeline and key developments
Full Stack Deep Learning - Production ML resources
Prompting Guide - Comprehensive prompt engineering guide
a16z AI Cannon - Curated list of AI resources
2025 AI Engineer Reading List - Latest papers and trends

🎨 Beyond LLMs

An image is worth 16x16 words - Transformers for image classification
2021
Stable Diffusion - Efficient image generation in latent space
2021

🌟 Easy Papers for Beginners

Great introduction to reasoning in LLMs
2022
Iterative refinement with self-feedback
2023