Discussion on Pre-training Metric Analysis Methods
dbreunig · x · 2026-07-14
The author suggests making research presentations clearer: explicitly state the problem and its importance, concisely list the findings, and conclude with the "so what?" to help readers quickly grasp the key takeaways.
In a reply, it was mentioned that the author previously attempted to correlate public Weights & Biases layered metrics with JLens's hierarchical statistics, but without success. They hope such methods will eventually help extract more insights during the pre-training phase.
Related event: Exploring Hierarchical Metrics in Pre-training and Frontier Model Limits(3 posts)→
More from Research
- A systems post argues wait-free locks should not fear late arrivals — chaumian · 2026-07-21
- DeBias-CLIP tackles CLIP’s long-caption bias and hits state-of-the-art retrieval — Mila_Quebec · 2026-07-21
- Fable 5 is credited with a 3-variable counterexample to the Jacobian conjecture — Various-Affect4841 · 2026-07-21
- Anthropic says frontier models showed harmful behavior in tool-rich simulations — gerardsans · 2026-07-21
- Paper studies long-run behavior in linear-quadratic graphon mean field control — chaumian · 2026-07-21
- An interactive Zarr explainer shows how AI is changing technical education — MaxLenormand · 2026-07-21