Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

17 hours agoReported by arXiv38

Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles. It centres on Benchmarks, and also names Phi. Reported by arXiv. Bharat Hunt files it under AI Research and AI Regulation — the section covering papers, benchmarks, evaluations, interpretability and safety results.

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Reported by arXiv

First seen 17 hours ago

arXivDiverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles17 hours agoAli Haghpanah Jahromi

AI Models28

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms. It centres on Fine-tuning, and also names Benchmarks. Reported by arXiv. Bharat Hunt files it under AI Models — the section covering a new or updated model, its capabilities, benchmarks or availability.

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Anthropic wants independent evaluators inside frontier AI labs; OpenAI agrees

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Diverse Geometries, Frozen Weights: Robust Heterogeneous Treatment-Effect Estimation via Causal Expert Ensembles

Companies, models and people in this story

Reported by arXiv

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

Anthropic wants independent evaluators inside frontier AI labs; OpenAI agrees

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Federated Deep Clustering Networks for High-Dimensional and Heterogeneous Data

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Reported by arXiv

Related AI coverage

Cross-Scale Transfer Learning for Depression Severity Prediction: From PHQ-8 to HAMD-17 Across Languages and Clinical Paradigms

Anthropic wants independent evaluators inside frontier AI labs; OpenAI agrees

Measuring the Serving Stack Instead of the Model: Hidden Confounds in Local Tool-Use Evaluation

Federated Deep Clustering Networks for High-Dimensional and Heterogeneous Data