Who is Model Adaptation?

Model Adaptation is when a model learns to work better in a new situation by using what it already knows.

Imagine you have a robot friend who loves to draw pictures. It learned how to draw cats by looking at lots of cat pictures. Now, it wants to learn how to draw dogs too. Instead of starting from scratch, it uses its knowledge about cats, like how ears and eyes look, and adjusts a little bit to make the new drawings of dogs work better. That’s model adaptation!

Think of it like learning a new game after knowing another one. If you know how to play soccer, it's easier to learn basketball because you already know how to move and pass the ball, you just need to adjust your rules.

In model adaptation, the model takes what it knows from one task, like drawing cats, and makes small changes so it can do something new, like drawing dogs. This saves time and energy, just like when you learn a new game by using skills from an old one!