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The Signal

Everything that matters in AI, with our take.

Updated through the day. Every headline links straight to the source. The two lines underneath are ours.

arXiv cs.CLPaper

Regime-Conditional Verification: Correctness Estimation for Adapting and Monitoring Safety Classifiers

This solves a real deployment problem: your safety classifier was trained on the model vendor's policy, but you need it to enforce yours. RCV makes that retrofit work without the cost of retraining, and also detects when the classifier's accuracy is drifting in production. If you're shipping an LLM with custom safety needs, this is a concrete technique to evaluate.

arXiv cs.AIPaper

PACE-Bench: Benchmarking Physics Adaptation via Code Evolution in Dynamic Environments

This is real. Agent adaptation under distribution shift is critical and understudy. The benchmark is substantial and the results show the problem isn't solved: state-of-the-art hits only 35% on full pairs. If you're building agents that need to recover from changed environments, this benchmark and its results matter. Use it to stress-test your approach.