> Likewise, asked to make Qwen3.5-0.8B better at math without gradients, Astra identifies an issue in its weights causing reasoning loops that Qwen’s own model card warns about, and fixes this by natively editing 0.016% of the weights.
How is that not misleading when the in the Qwen case “natively editing” refers to a mere directional ablation, a well-known technique that has been used a ton by both academics and hobbyists over the past few years?
Regarding the "extend beyond what we'd expect from humans..." Do you know people that could do 4 & 5? I'd love to see a challenge on problems like this where we take a frontier model against top AI researchers - I don't think any human is winning this challenge.
I can't believe that you genuinely don't find misleading that they used the same phrase for "reading and editing a text representation of the weights" without any tools and "mechanically apply a python-computed steering vector to the weights", and I don't have time to waste with bad faith shills.
Good day.