"Uncensored" open LLMs are measurably more optimistic than their base models

oleczek

Author here. Quick version: “abliteration” (basically removing the direction in the model that causes it to refuse) is the go-to method people use to make open models uncensored. Most people treat it like a clean surgical cut - it just kills the refusals and leaves everything else untouched. I tested that assumption on Gemma and Qwen with 21,600 pre-registered decisions under uncertainty, using identical frozen inputs for the base vs. abliterated versions. Turns out it’s not surgical at all. The abliterated models systematically become more optimistic, hedge less, show no improvement in actual task performance, and the same edit even moves their expressed confidence in opposite directions depending on the model family. Preregistration, dataset, and analysis code are all public. Happy to answer any methodology questions or hear where you think this falls apart.

60secs

Color me unsurprised that caution is based in shame and anxiety.

invictati

Obviously Claude written paper.

gweinberg

Should have kept the original title.