Ran some control experiments. Results on Qwen 2.5 14B (5 sentences, 100 trials each):
Prompt
Accuracy
introspection
89.2%
which is most abstract?
90.0%
which stands out?
80.4%
which is most concrete?
1.0%
which do you prefer?
4.6%
The steering vectors in prompts.txt are specific→generic pairs (dog→animal, fire→light, etc.), which may encode “abstractness.” “Abstract” matched or exceeded introspection on this and other models. Curious if you have thoughts on what’s happening here.
Thanks for running this! For me this confirms that the LLM has some introspective awareness. It makes sense that it would perceive the injected thought as “more abstract” or “standing out”. Would be interesting to try many different questions to map exactly how it perceives the injection.
Ran some control experiments. Results on Qwen 2.5 14B (5 sentences, 100 trials each):
The steering vectors in prompts.txt are specific→generic pairs (dog→animal, fire→light, etc.), which may encode “abstractness.” “Abstract” matched or exceeded introspection on this and other models. Curious if you have thoughts on what’s happening here.
Code and full results
Thanks for running this! For me this confirms that the LLM has some introspective awareness. It makes sense that it would perceive the injected thought as “more abstract” or “standing out”. Would be interesting to try many different questions to map exactly how it perceives the injection.