pr0mila/From-GANs-to-RAG-A-Journey-Through-Modern-Deep-Learning
A curated collection of foundational papers tracing the evolution from early generative models to modern retrieval-augmented language systems.
This collection provides a structured reading path through 14 essential research papers that illustrate the evolution of modern deep learning. It guides you from early generative models, showing how neural networks learned to create, all the way to advanced retrieval-augmented language systems that combine reasoning with external knowledge. This is for AI researchers, students, and practitioners who want to understand the conceptual progression of major breakthroughs in AI.
Use this if you want to understand the historical and conceptual development of generative AI and large language models by reading the foundational papers in a logical sequence.
Not ideal if you're looking for practical code implementations, quick-start tutorials, or a survey of the latest minor advancements in AI.
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Dec 13, 2025
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