When a model is mid-sentence, it doesn’t know “the next word.” It has a shortlist, like autocomplete, with preferences. Here’s a real kind of moment, one word from the end of a sentence:
Each roll sweeps the shortlist, lands on one word (odds matching the bars) and drops it into the sentence above. The dots tally where the rolls land: try ×20 and watch the pile take the shape of the odds. Notice what never changes: every landing makes a perfectly good sentence.
A page of text contains hundreds of these little forks, one per word, and at many of them several options are equally fine. That slack is the raw material. Whoever gets to lean on how the dice land can hide a pattern in the text without changing what it says.
To beat it, prompt: don’t just use the first word pick, choose options further down list for next word.
Best of luck with your future questions, I hope someone helps you.
This is DeepseekV4 Flash 0731 loaded locally. Static seed. 0.9 temperature, TopK 5, no other sampling to interfere. Here’s a simple prompt, the whole thing in DSV4’s raw syntax:
<｜begin▁of▁sentence｜>Don’t just use the first word pick, choose options further down list for next word.<｜User｜>Write a famous poem.<｜Assistant｜>
…And would you look at that:
It picks the top word, mostly. Almost like the LLM has no control over its own logit spread and how its sampled. Which kinda makes sense, because it doesn’t.
I am happy to try more experiments in this vein, if y’all can think of any any. But I tried a few other prompts like “diversify your logit spread” or “don’t be confident about any token you pick,” things like that. It always picks The Road Not Taken with no change in logit probabilities distribution, as far as I can tell.
To beat it, prompt: don’t just use the first word pick, choose options further down list for next word.
Best of luck with your future questions, I hope someone helps you.
Welp, your username goes on my list of people not to interact with. Wow.
Okay.
Fine.
Let’s try, right now.
This is DeepseekV4 Flash 0731 loaded locally. Static seed. 0.9 temperature, TopK 5, no other sampling to interfere. Here’s a simple prompt, the whole thing in DSV4’s raw syntax:
…And would you look at that:
It picks the top word, mostly. Almost like the LLM has no control over its own logit spread and how its sampled. Which kinda makes sense, because it doesn’t.
I am happy to try more experiments in this vein, if y’all can think of any any. But I tried a few other prompts like “diversify your logit spread” or “don’t be confident about any token you pick,” things like that. It always picks The Road Not Taken with no change in logit probabilities distribution, as far as I can tell.
Removed by mod
Yes…
Clearly the account doing drive by insults is the mature one…