Tag: causal machine learning
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Neural Networks for Accurate Text-to-Speech Evaluation
Explore neural network models that improve Text-to-Speech evaluation accuracy, surpassing human benchmarks in MOS and SBS assessments.
Improving Open-Set Text Classification with Uncertainty Estimation
Discover how uncertainty estimation enhances accuracy and reliability in open-set text classification systems using the HolUE method.
EMA Limits in Sequence Models: Balancing Structure & Content
Explore EMA's role and limits in sequence models, revealing the need for input-dependent selection to improve temporal structure encoding and reduce inform...
GNN-as-Judge: Enhancing Graph Learning with LLM Feedback
Discover how GNN-as-Judge boosts graph learning by combining LLMs and GNNs for reliable pseudo labels and reduced noise in low-resource settings.
Effective Divergence Measures for Training GFlowNets
Explore optimized divergence measures to enhance GFlowNets training, improving convergence speed and sampling accuracy in generative modeling.