Autoregressive language models are often used to generate samples, but many applications depend on the expected value of some function of the output. Computing that expectation directly is hard, and the new preprint argues that doing so reliably can be computationally expensive.
The authors say they show "how to" address this problem, but the abstract cuts off at that point, so the specific method is not described in the available text. No further details about the approach or experimental results are given in the source.
Because there is only one source, there are no conflicting findings to compare. The paper is posted on arXiv under identifier 2610.11399.