100 years ago most scientific papers were written in German. I wonder when the switch to Chinese will happen.
"Made in China, designed by Apple in California"
should be:
"Made in China, designed by Chinese people in California"?
They seemed like they had to be churning out papers and any little adaptation to existing research triggered a new publication.
But it may have changed now.
But to filter based on author's names sounds pretty darn racist.
I suppose we just don't have a deeper underlying theory to lean on and help us 'design' anything.
We really need to develop better tools to understand what's happening inside these NNs. Working with high-D spaces is not something we're good at, and we're basically throwing stuff at it and seeing if it sticks.
Title should be: Simple Self-Distillation Improves Code Generation
Many computer science paper titles allude to past titles in other CS papers.
Calling it “cringe worthy” is unnecessarily mean. There is context and history you don’t understand.
> Code interleaves fork positions, where several continuations are genuinely plausible and may correspond to different solution approaches, with lock positions, where syntax and semantics leave little ambiguity but a low-probability distractor tail still remains… The best global decoding setting is therefore necessarily a compromise; we call this tension the precision-exploration conflict.
In other words, just like us, the model needs to shift from "exploration" in "fork" mode (divergent thinking to produce a creative solution) to "precision" in "lock" mode (producing syntactically correct code).
What this paper shows is that their simple technique (SSD) can improve the ranking of optimal tokens in both lock and fork positions, meaning the model is more likely to explore when it should be exploring, and more likely to be precise when it needs to be.
I love that we're still learning the emergent properties of LLMs!
That already looks like Sonnet 3x and 4 level capabilities to me where the model in question (Gemma 4) set ups whole python project with a UI and installs python libraries using uv etc.
Add this Simple Self Distillation to the picture and by 2028 I see cheaper coding model providers with much more generous usage limits in the future and power users would be mostly running their own models anyway.
Anyone using these models as "non-deterministic transpilers" from natural language to code (experienced engineers who can write code themselves) would probably not be paying to any AI providers.
jofzar•34m ago
Sorry apple, SSD is already taken, you can't use that acronym.
ape4•30m ago
love2read•28m ago
Consistency Preservation Update (CPU)
Guided Probability Update (GPU)
History-aware Distillation Driving (HDD)
Probability Smoothing Update (PSU)