Reading List
A collection of papers, articles, tutorials, and resources I find interesting and useful. These are things I've read, studied, or played with in the areas of machine learning, AI systems, and software engineering.
CWM
MetaWorld Model
Open weights world model from Meta AI research.
Hands-on Model Serving
O'ReillyModel Serving
Comprehensive guide on deploying ML models to production.
Building a Reasoning Model From Scratch
Sebastian RaschkaReasoning
Step-by-step guide to building reasoning capabilities in LLMs.
RAGPack
Jay AlammarRLVR
Advanced RAG techniques and RLVR methods.
Attention Is All You Need
Vaswani et al.LLM
The foundational transformer paper.
ReAct: Synergizing Reasoning and Acting
Yao et al.Agents
Key paper on combining reasoning with tool use in LLMs.
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Lewis et al.RAG
The original RAG paper from Facebook AI.
LoRA: Low-Rank Adaptation of Large Language Models
Hu et al.Fine-tuning
Efficient fine-tuning method that's become standard practice.