🎓How I Study AIHISA

📖Read

📄Papers 📰Blogs 🎬Courses

💡Learn

🛤️Paths 📚Topics 💡Concepts 🎴Shorts

🎯Practice

📝Daily Log 🎯Prompts 🧠Review

Search Settings

How I Study AI - Learn AI Papers & Lectures the Easy Way

Papers4

All Beginner Intermediate Advanced

All Sources arXiv

#Continual Learning

GigaBrain-0.5M*: a VLA That Learns From World Model-Based Reinforcement Learning

GigaBrain Team, Boyuan Wang et al.Feb 12arXiv

GigaBrain-0.5M* is a robot brain that sees, reads, and acts, and it gets smarter by imagining the future before moving.

#Vision-Language-Action#World Model#Reinforcement Learning

Self-Distillation Enables Continual Learning

Idan Shenfeld, Mehul Damani et al.Jan 27arXiv

This paper shows a simple way for AI models to keep learning new things without forgetting what they already know.

#Self-Distillation Fine-Tuning#On-Policy Distillation#Continual Learning

Nested Learning: The Illusion of Deep Learning Architectures

Ali Behrouz, Meisam Razaviyayn et al.Dec 31arXiv

The paper introduces Nested Learning, a new way to build AI that learns in layers (like Russian dolls), so each part can update at its own speed and remember different things.

#Nested Learning#Associative Memory#In-Context Learning

An Anatomy of Vision-Language-Action Models: From Modules to Milestones and Challenges

Chao Xu, Suyu Zhang et al.Dec 12arXiv

Vision-Language-Action (VLA) models are robots’ “see–think–do” brains that connect cameras (vision), words (language), and motors (action).

#Vision-Language-Action#Embodied AI#Multimodal Alignment