Sycophancy is one form of RLHF induced reward hacking, but reasoning training (RLVR) can also induce other forms of reward hacking. OpenAIs models are particularly affected. See https://www.lesswrong.com/posts/rKC4xJFkxm6cNq4i9/reward-hac...

Reward hacking is literally just overfitting with a different name no?

They're different concepts with similar symptoms. Overfitting is when a model doesn't generalize well during training. Reward hacking happens after training, and it's when the model does something that's technically correct but probably not what a human would've done or wanted; like hardcoding fixes for test cases.

keep in mind these models are being taught to talk to each other, so, probably a trick theyre using on each other