Tag: causal machine learning
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Target-Aligned Reinforcement Learning for Faster Convergence
Discover how Target-Aligned Reinforcement Learning (TARL) improves stability and accelerates convergence in RL algorithms with proven benchmark results.
Efficient Uncertainty Quantification Using Gradient Norms
Discover an efficient isotropic method for uncertainty quantification in large language models using gradient norms and a single model pass.
Few-Shot Writer Adaptation for Handwritten Text Recognition
Discover few-shot writer adaptation via multimodal in-context learning to improve handwritten text recognition without complex updates or tuning.
Hallucination-Free Edits in Large Vision-Language Models
Discover a novel framework for dynamic hallucination detection and efficient edits in large vision-language models, improving accuracy with minimal cost.
CIPHER: Advanced Deepfake Detection for Synthetic Images
Discover CIPHER, a robust framework using GAN discriminators to detect deepfake images with high accuracy across multiple generative models.