#meta-learning2 articles

2 articles

AIBullisharXiv – CS AI · 4h ago4

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Alignment through Meta-Weighted Online Sampling: Bridging the Gap between Data Generation and Preference Optimization

Researchers propose MetaAPO, a new framework for aligning large language models with human preferences that dynamically balances online and offline training data. The method uses a meta-learner to evaluate when on-policy sampling is beneficial, resulting in better performance while reducing online annotation costs by 42%.

AINeutralarXiv – CS AI · 4h ago6

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Test-Time Training with KV Binding Is Secretly Linear Attention

Researchers reveal that Test-Time Training (TTT) with KV binding, previously understood as online meta-learning for memorization, can actually be reformulated as a learned linear attention operator. This new perspective explains previously puzzling behaviors and enables architectural simplifications and efficiency improvements.