NLP Archives - AI Papers Academy

Google Nested Learning Explained: Hope Architecture, Continual Learning, and the End of Frozen LLMs

Google’s Nested Learning paper and Hope model explained: a new approach to continual learning in LLMs that addresses catastrophic forgetting.

GDPO is NVIDIA’s solution to GRPO’s limitations in multi-reward RL for large language models. We break down the paper in this post.

Manifold-Constrained Hyper-Connections (mHC) explained: How DeepSeek rewires residual connections in LLMs for next-gen AI

Discover how reinforcement learning enables hierarchical reasoning in LLMs and how HICRA improves on top of GRPO.

In this post, we break down the TRM paper, a simpler version of the HRM, that beats HRM and top reasoning LLMs with a tiny 7M params model.

In this post we break down the Hierarchical Reasoning Model (HRM), a new model that rivals top LLMs on reasoning benchmarks with only 27M params!

In this post we break down Microsoft’s Reinforcement Pre-Training, which scales up reinforcement learninng with next-token reasoning

In this post we explain the Darwin Gödel Machine, a novel method for self-improving AI agents by Sakana AI

Dive into Continuous Thought Machines, a novel architecture that strive to push AI closer to how the human brain works

Dive into Perception Language Models by Meta, a family of fully open SOTA vision-language models with detailed visual understanding