Tag: causal machine learning
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TFRBench: Benchmark for Reasoning in Forecasting AI
Discover TFRBench, the first benchmark assessing reasoning in forecasting systems to improve AI accuracy and interpretability.
Reducing Sycophancy in Language Models with Reward Decomposition
Discover how reward decomposition helps language models resist social pressure and improve factual accuracy, enhancing AI reliability and trustworthiness.
Attribution Bias in Large Language Models: Key Insights
Explore attribution bias in large language models with AttriBench, revealing demographic disparities and challenges in fair quote attribution.
IntentScore: Enhancing Action Evaluation for Computer Agents
Discover IntentScore, a plan-aware model improving action quality evaluation in computer-use agents, boosting task success and reducing errors.
Algebraic Framework for Real-World Combinatorial Optimization
Discover how algebraic structures and quotient space learning improve real-world combinatorial optimization efficiency and solution quality.