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Study Notes

AI paper notes

A curated view of AI papers and technical reports from my Notion notes. RAG and LLM systems stay upfront, while recommender systems and deep learning classics are grouped as supporting foundations.

Topics

RAG

Retrieval quality, graph structure, and long-context limits.

LightRAG: Simple and Fast Retrieval-Augmented Generation GraphRAG cost, dual-level retrieval, and incremental updates
Lost in the Middle Why models miss information placed in the middle of long context
A Graph RAG Approach to Query-Focused Summarization Graph-based summarization over global document structure
Engineering RAG Systems for Real-World Applications Evaluation and operational concerns for production RAG

LLM

Transformer structure, long-context behavior, and inference stability.

Attention Is All You Need The Transformer core and how modern LLM stacks evolved from it
Context Rot: How Increasing Input Tokens Impacts LLM Performance How longer input can reduce reliability and reasoning quality
Defeating Nondeterminism in LLM Inference Reproducibility and nondeterminism in LLM inference
Small Language Models are the Future of Agentic AI Why smaller models can matter in agent workflows

Generative Models

Image generation, diffusion, and visual understanding papers.

Diffusion Models Beat GANs on Image Synthesis Why diffusion models became strong image synthesis baselines
MIRAGE: The Illusion of Visual Understanding Limits and evaluation questions for vision-language models

Foundations

Classic deep learning papers connected back to modern model design.

ImageNet Classification with Deep Convolutional Neural Networks AlexNet and the start of large-scale image classification
Batch Normalization Training stability and normalization in deep networks
Deep Residual Learning for Image Recognition How residual connections changed deep model training

Recommender Systems

Recommendation models through retrieval, ranking, and personalization.

Deep Neural Networks for YouTube Recommendations Candidate generation and ranking in large-scale recommendation
Deep Learning based Recommender System: A Survey Major architectures and research directions in deep recommender systems
Dynamic Multi-Behavior Sequence Modeling for Next Item Recommendation Using multi-behavior sequences for next item recommendation