3 papers
cs.LG2025
General Information Metrics for Improving AI Model Training Efficiency
Jianfeng Xu, Congcong Liu, Xiaoying Tan +8
To address the growing size of AI model training data and the lack of a universal data selection methodology-factors that significantly drive up training costs -- this paper presen…
cs.LG2024
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression
Anpeng Wu, Kun Kuang, Ruoxuan Xiong +4
In causal inference, encouragement designs (EDs) are widely used to analyze causal effects, when randomized controlled trials (RCTs) are impractical or compliance to treatment cann…
cs.CL2024
Causality for Large Language Models
Anpeng Wu, Kun Kuang, Minqin Zhu +7
Recent breakthroughs in artificial intelligence have driven a paradigm shift, where large language models (LLMs) with billions or trillions of parameters are trained on vast datase…