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.

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arXiv cs.AIPaper7d ago

One Loop, Two Gains: Can Active Learning win the Lottery for Free?

This exploits an existing computational loop to solve two problems at once: finding winning lottery tickets and acquiring labels efficiently. Clever but narrow. It matters only if you're doing both active learning and network compression on the same project, which is not most builders.

research pruning active-learning

arXiv cs.LGPaper13d ago

Subspace Inference Enables Efficient Active Reward Learning from Preferences

The core idea—active learning needs uncertainty quantification, and full posterior over large networks is expensive—is sound, but the execution is specialist. If you're training reward models at scale with human feedback, this Kalman filtering approach could cut query counts. For most teams, vanilla RLHF still works; this is an optimization for high-volume settings.

research rlhf active-learning reward-modeling