Likelihood hacking in probabilistic program synthesis
arXiv:2603.24126v1 Announce Type: new
Abstract: When language models are trained by reinforcement learning (RL) to write probabilistic programs, they can artificially inflate their marginal-likelihood reward by producing programs whose data distributi…