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Activation probes can predict future behaviors in reasoning models with up to 91% accuracy, enabling effective steering without sacrificing output quality.
Framework choice in multi-agent systems matters just as much as the LLM itself, a fact obscured by existing model-centric benchmarks.
Forget training on just images or text – TAIL, a new meta-learner, masters both and extrapolates to 20x more classes, all while slashing compute costs.
