Six AI Papers That Changed Everything in Under 15 Pages: From Dropout to LoRA
cneuralnetwork · x · 2026-11-11
A curated list of landmark AI/CS papers that are short enough to read in one sitting:
- Dropout (2012): just 2 pages, a simple trick to reduce neural network overfitting
- Adam (2014): 9 pages, the optimizer behind countless deep learning models
- LoRA (2021): 8 pages, fine-tuning large models via low-rank updates
- MapReduce (2004): 13 pages, how Google processed massive datasets across thousands of machines
- The Google File System (2003): 15 pages, the foundation of distributed storage at scale
- A Mathematical Theory of Communication (1948): the foundational information theory paper, notably longer
The takeaway: some of the most influential research in the field is remarkably concise.
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