Tag: weak
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Limitations of refinement methods for weak to strong generalization
Limitations of refinement methods for weak to strong generalization arXiv:2508.17018v1 Announce Type: new Abstract: Standard techniques for aligning large language models (LLMs) utilize human-produced data, which could limit the capability of any aligned LLM to human level. Label refinement and weak training have emerged as promising strategies to address this superalignment problem. In this work,…
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Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities
Reliable Programmatic Weak Supervision with Confidence Intervals for Label Probabilities arXiv:2508.03896v1 Announce Type: new Abstract: The accurate labeling of datasets is often both costly and time-consuming. Given an unlabeled dataset, programmatic weak supervision obtains probabilistic predictions for the labels by leveraging multiple weak labeling functions (LFs) that provide rough guesses for labels. Weak LFs commonly…
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The surprising strength of weak classifiers for validating neural posterior estimates
The surprising strength of weak classifiers for validating neural posterior estimates arXiv:2507.17026v1 Announce Type: new Abstract: Neural Posterior Estimation (NPE) has emerged as a powerful approach for amortized Bayesian inference when the true posterior $p(theta mid y)$ is intractable or difficult to sample. But evaluating the accuracy of neural posterior estimates remains challenging, with existing…