MIT CSAIL researchers say GPT-6 Astra edited 0.016% of Qwen3.5-0.8B weights to fix reasoning loops, lifting MATH-500 from 7.9% to 48.1% without training.
Foundry in the real world: Turning LLM hunches into verified findings – Security Loop Series, Part 2
See how Foundry turns LLM hunches into verified findings on Langflow, MLflow, and PyGoat, using an evidence gate and an honest look at token cost.
MIT has unveiled an innovative, groundbreaking paradigm dubbed "Weight Space Programming", representing a transformative new ...
Astra identifies game policies from raw weight matrices and fixes reasoning loops in Qwen3.5-0.8B by editing 0.016% of parameters, lifting MATH-500 scores from 7.9% to 48.1% without training loops.
A comprehensive guide to the platforms, APIs, and specialist tools that convert unstructured documents into structured, actionable data.
A new MIT CSAIL blog post is making the rounds in AI circles this week, and it describes something that sounds almost ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results