Journal of Applied Language Learning(JALL)

Ph. D. of Tel Aviv University, The Lester and Sally Antin Faculty of Humanities, School of Philosoph, Israel

Publications

• Review Article   
  Beyond Statistical Fairness: A Three-Layer Framework for Benchmark-Independent Evaluation of Semantic Debiasing
  Author(s): Yair Oppenheim*
  
  The rapid deployment of Large Language Models (LLMs) has intensified concerns regarding demographic bias and semantic unfairness in generated text. Existing evaluation methodologies primarily assess fairness through benchmark- specific performance or statistical significance, providing limited evidence regarding whether semantic debiasing methods remain effective across heterogeneous benchmark ecosystems. Consequently, current evaluation approaches often fail to distinguish benchmark optimization from genuine benchmark-independent semantic fairness. This paper introduces a comprehensive three-layer evaluation framework for semantic debiasing and validates it through the Dynamic Bias Semantic Debiasing (DBSD) framework. The proposed methodology integrates three complementary evaluation layers: (1) Semantic Effectiveness, which quantifies semantic bias reducti.. Read More»
  

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