Source list

Courses

• Stanford CS336 — Language Modeling from Scratch, Spring 2025, Percy Liang & Tatsunori Hashimoto. cs336.stanford.edu/spring2025. Full lectures on YouTube (Reddit announcement, July 11, 2025).
• Stanford CS25 — Transformers United V5. web.stanford.edu/class/cs25.
• Stanford CS231n — Deep Learning for Computer Vision, Spring 2024. cs231n.stanford.edu.
• Stanford ENGR319 — Foundations of Generative AI. online.stanford.edu.
• CMU 11-868 — Large Language Model Systems, Spring 2025, Lei Li. llmsystem.github.io/llmsystem2025spring.
• Berkeley CS 285 — Deep Reinforcement Learning, Fall 2024, Sergey Levine. rail.eecs.berkeley.edu/deeprlcourse.
• Berkeley CS 294-277 — Robots that Learn, Spring 2026, Jitendra Malik. Original announcement: Malik on X, Jan 6, 2025.
• MIT 6.S191 — Introduction to Deep Learning, 2025. introtodeeplearning.com.
• NVIDIA Deep Learning Institute — Robotics Fundamentals and Generative AI Teaching Kit. nvidia.com/training.
• 500 Global VC Unlocked: Silicon Valley (Aug 24 – Sept 4, 2026, Stanford campus, $25K). 500.co/vcu/stanford.
• 500 Global VC Unlocked: AI Edition. 500.co/vcu/ai.

Foundational papers

• Vaswani et al., Attention Is All You Need, arXiv:1706.03762, June 12, 2017.
• He et al., Deep Residual Learning for Image Recognition, arXiv:1512.03385, Dec 10, 2015.
• Dosovitskiy et al., An Image is Worth 16×16 Words (ViT), arXiv:2010.11929, Oct 22, 2020.
• Su et al., RoFormer: Enhanced Transformer with Rotary Position Embedding, arXiv:2104.09864, April 20, 2021.
• Schulman et al., Proximal Policy Optimization Algorithms, arXiv:1707.06347, July 20, 2017.
• Haarnoja et al., Soft Actor-Critic, arXiv:1801.01290, Jan 4, 2018.
• Hoffmann et al., Training Compute-Optimal LLMs (Chinchilla), arXiv:2203.15556, March 29, 2022.

LLM systems & alignment

• Dao et al., FlashAttention-2, arXiv:2307.08691, July 17, 2023.
• Kwon et al., PagedAttention / vLLM, arXiv:2309.06180, Sept 12, 2023.
• Zheng et al., SGLang, arXiv:2312.07104, Dec 12, 2023.
• Frantar et al., GPTQ, arXiv:2210.17323, Oct 31, 2022.
• Leviathan et al., Speculative Decoding, arXiv:2211.17192, Nov 30, 2022.
• Rafailov et al., Direct Preference Optimization, arXiv:2305.18290, May 29, 2023.
• DeepSeek-AI, DeepSeek-V3 Technical Report, arXiv:2412.19437, Dec 27, 2024.
• DeepSeek-AI, DeepSeek-R1, arXiv:2501.12948, Jan 22, 2025.
• Meta AI, The Llama 3 Herd, arXiv:2407.21783, July 31, 2024.
• Penedo et al., The FineWeb Datasets, arXiv:2406.17557, June 25, 2024.
• Zhao et al., PyTorch FSDP, arXiv:2304.11277, April 21, 2023.
• Liu et al., Ring Attention, arXiv:2310.01889, Oct 3, 2023.
• Anthropic, Introducing Contextual Retrieval, Sept 19, 2024.
• Microsoft Research, GraphRAG, arXiv:2404.16130, April 24, 2024.
• Greshake et al., Indirect Prompt Injection, arXiv:2302.12173, Feb 23, 2023.
• Amodei et al., Concrete Problems in AI Safety, arXiv:1606.06565, June 21, 2016.

Inference & infrastructure

• Red Hat Developer, Introduction to distributed inference with llm-d, Nov 21, 2025.
• Red Hat Developer, llm-d: Kubernetes-native distributed inferencing, May 20, 2025.
• llm-d project. llm-d.ai.
• vLLM documentation. docs.vllm.ai.
• Triton documentation. triton-lang.org.
• PyTorch Autograd Mechanics. docs.pytorch.org.
• NVIDIA H100 Architecture Whitepaper, March 22, 2022.
• NVIDIA Blackwell Architecture Brief, March 18, 2024.

Agent protocols & orchestration

• Anthropic, Model Context Protocol specification, modelcontextprotocol.io.
• Google, Agent2Agent (A2A) Protocol, google.github.io/A2A, April 9, 2025.
• LangGraph documentation. langchain-ai.github.io/langgraph.
• OWASP Top 10 for LLM Applications. owasp.org/llm-top-10.

Vision & 3D

• Radford et al., CLIP, arXiv:2103.00020, Feb 26, 2021.
• Zhai et al., SigLIP, arXiv:2303.15343, March 27, 2023.
• Oquab et al., DINOv2, arXiv:2304.07193, April 14, 2023.
• Mildenhall et al., NeRF, arXiv:2003.08934, March 19, 2020.
• Kerbl et al., 3D Gaussian Splatting, arXiv:2308.04079, Aug 8, 2023.
• Meta AI, SAM 2, arXiv:2408.00714, Aug 1, 2024.

Robotics & VLAs

• Lynch & Park, Modern Robotics: Mechanics, Planning, and Control, Cambridge University Press, 2017. hades.mech.northwestern.edu.
• Tobin et al., Domain Randomization, arXiv:1703.06907, March 20, 2017.
• Chi et al., Diffusion Policy, arXiv:2303.04137, March 7, 2023.
• Brohan et al., RT-2, robotics-transformer2.github.io, 2023.
• Kim et al., OpenVLA, arXiv:2406.09246, June 13, 2024. Project: openvla.github.io.
• Physical Intelligence, π0, HF blog, Feb 4, 2025.
• Physical Intelligence, π0.5: a VLA with Open-World Generalization, arXiv:2504.16054, April 22, 2025.
• Hugging Face, SmolVLA, HF blog, June 3, 2025. Model: lerobot/smolvla_base.
• NVIDIA Research, GR00T N1, March 18, 2025.
• NVIDIA Research, GR00T N1.5, research.nvidia.com/labs/gear/gr00t-n1_5, June 11, 2025.
• NVIDIA Isaac Lab. isaac-sim.github.io/IsaacLab.
• NVIDIA Isaac GR00T GitHub. github.com/NVIDIA/Isaac-GR00T.
• Hugging Face LeRobot. github.com/huggingface/lerobot.
• MuJoCo documentation. mujoco.readthedocs.io.
• Qi et al., Visual Adversarial Examples Jailbreak Aligned LLMs, arXiv:2306.13213, June 22, 2023.

Books

• Goodfellow, Bengio & Courville, Deep Learning, MIT Press, 2016. deeplearningbook.org.
• Sutton & Barto, Reinforcement Learning: An Introduction, 2nd ed., MIT Press, 2018. incompleteideas.net/book.
• Cover & Thomas, Elements of Information Theory, 2nd ed., Wiley, 2006.