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Skill RSI is a free tool that recursively evaluates and improves AI skills via procedural evaluations and a research agent, supporting standalone or Codex plugin usage.
A blog post from Flyback demonstrates how a LightGBM feature that ranked #1 in importance actually worsened predictions due to target encoding leakage, highlighting the danger of relying solely on feature importance metrics.
This paper investigates how post-training of LLMs introduces AI-like stylistic regularities and proposes PASTA, a training-free method to localize and ablate these alignment signatures, reducing AI detection rates while maintaining coherence across 11 models and 6 detectors.
Nous Research released Contrastive Neuron Attribution (CNA), a method to steer LLM behavior by identifying and ablating sparse circuits in MLP neurons without training sparse autoencoders or degrading general benchmarks, validated on multiple large language models.