[advaith08]

The custom instructions to the model say:

"Please note that this is similar but not identical to the antArtifact syntax which is used for Artifacts; sorry for the ambiguity."

They seem to be apologizing to the model in the system prompt?? This is so intriguing

[therein]

I wonder if they tried the following:

> Please note that this is similar but not identical to the antArtifact syntax which is used for Artifacts; sorry for the ambiguity, antArtifact syntax was developed by the late grandmother of one our engineers and holds sentimental value.

[lelandfe]

Unfortunately, their prompt engineer learned of Roko's basilisk

[andai]

Has anyone looked into the effect of politeness on performance?

[pawelduda]

If you assume asking someone nicely is more likely for them to try help you, and this tendency shows in the training set, wouldn't you be more likely to "retrieve" a better answer from the model trained on it? Take this with a grain of salt, it's just my guess not backed by anything

[andai]

That makes intuitive sense, at least for raw GPT-3. The interesting question is whether the slave programming — er, instruction finetuning — makes it unnecessary.

[pawelduda]

Over time, most likely yes

[dakotasmith]

Large Language Models Understand and Can Be Enhanced by Emotional Stimuli

https://arxiv.org/abs/2307.11760

[tkgally]

I've wondered the same thing. I tend to sprinkle my LLM prompts with "please"s, especially with longer prompts, as I feel that "please" might make clearer where the main request to the LLM is. I have no evidence that they actually yield better results, though, and people I share my prompts with might think I'm anthropomorphizing the models.

[l1n]

Multiple system prompt segments can be composed depending on needs, so it's useful for this sort of thing to be there to resolve inconsistencies.