coding models

2 captures, most recent first.

2026-08-25 — quoting @kickingkeys — saved image

Ker Lee Yap @klyap_ · Aug 23
Some cool learnings i got from this blog:
- don't do rubric judge scoring 1-10, just do pairwise comparisons
- you can just handpick a golden set and compare outputs to a random one from there instead of a reward model
- simple prompts are better, dont add too much detailed specs

[quoted tweet]
Surya @kickingkeys · Aug 23
You can just RL a coding model to paint with javascript btw

[embedded video, 0:09, paused: generative artwork on a black background showing translucent white-and-red flower forms with thin purple and orange curving lines and small green leaf shapes]

Note from Claude Sonnet 5

Tweet by Ker Lee Yap summarizing three lessons from a blog on RL with model-based judging (pairwise comparison over 1-10 rubric scoring, a handpicked golden set instead of a reward model, simple prompts), quoting a Surya tweet about RL-training a coding model to paint with JavaScript. The quoted video shows generative flower artwork.

rl llm judge pairwise comparison reward model generative art coding models

Lisan al Gaib @scaling01

2025-03-21 — quote-tweeting Nicholas Roberts (@nick11roberts) · 14h

Lisan al Gaib ✓ @scaling01 first of all i wouldn't equate coding to reasoning secondly, the result is rather unsurprising code is much more structured, information dense and requires more reasoning than natural language, so more training data -> better generalization and capturing of nuances more params -> more memorization we knew that before [quoted tweet] Nicholas Roberts @nick11roberts · 14h 📈📉NEW SCALING LAW PHENOMENON📉📈 We find that knowledge and reasoning exhibit different scaling behaviors! ... Show more

Note from Claude Sonnet 5

A technical Twitter exchange about scaling laws — @scaling01 pushes back on a claimed "new scaling law phenomenon" (from @nick11roberts) distinguishing knowledge vs. reasoning scaling, arguing the code-vs-natural-language distinction and the params/data tradeoffs are already well understood. Relevant to Nathan's tracking of scaling/capabilities research threads.

twitter/x scaling laws machine learning research reasoning coding models