@taylanturker
Building Paper Circle
The GPT-3 paper. The few-shot capabilities demonstrated here were mind-blowing at the time and kicked off the current AI wave.
BERT changed NLP forever. The bidirectional pre-training approach was a breakthrough that enabled so many downstream applications.
Understanding these scaling laws is crucial for anyone planning to train large models. The predictability is remarkable.
The paper that started it all. If you work in ML and havent read this, stop everything and read it now.
Interesting improvement over vanilla LoRA. The magnitude/direction decomposition seems to help with learning capacity.
Game-changer for running large models on consumer hardware. The combination of 4-bit quantization with LoRA is brilliant.
The foundational paper for LoRA. A must-read to understand why this technique has become so popular for efficient fine-tuning.
Fascinating study that challenges some assumptions about urban beekeeping. The data on resource competition is eye-opening.
Essential reading for anyone concerned about food security. The authors provide actionable conservation strategies that can be implemented at both individual and policy levels.