AI Papers Academy, Author at AI Papers Academy

LeCun’s LeWorldModel Explained: Finally a Stable JEPA World Model?

In this post, we break down LeWorldModel (LeWM), a new JEPA world model, introduced in a paper co-authored by Yann LeCun.

A deep data analysis of arXiv reveals the defining AI research trends of mid-2026: the agentic boom, Qwen overtaking Llama, and what’s fading

A breakdown of Microsoft’s SkillOpt paper, which applies gradient-descent-like optimization to continuously improve AI agent skills.

In this post, we break down DeepSeek-V4, a new LLM from DeepSeek designed for highly efficient reasoning over million-token contexts

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 Meta AI’s DINOv3 research paper, which introduces a state-of-the-art Computer Vision foundation models family