Deep-Learning

This article introduces Titans, a novel architecture that as a meta in-context learner, learns to memorize at test time. Through designing a long-term memory module, and proposing three variants of Titans (MAC, MAG, MAL), the model achieves superior performance compared to Transformers and other baselines, especially in long-context tasks.

This is the second part of the Natural Language Processing Series. It covers modern approaches in natural language processing, including RNNs, VAE-LMs, Transformer, BERT, GPT, GAN-LMs, In-Context Learning, CoT, RLHF, DPO, etc.