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Auditing Large Language Models for Enhanced Text-Based Stereotype Detection and Probing-Based Bias Evaluation
Recent advancements in Large Language Models (LLMs) have significantly increased their presence in human-facing Artificial Intelligence (AI) applications.
Eliciting Personality Traits in Large Language Models
However, whereas LMs with fewer parameters exhibit similar behaviour in personality traits, newer and LMs with more parameters exhibit a broader range of personality traits, with increased agreeableness, emotional stability, and openness.
Towards Auditing Large Language Models: Improving Text-based Stereotype Detection
In summary, our work establishes a robust and practical framework for auditing and evaluating the stereotypic bias in LLM.
A Machine Learning-based Recommendation System for Swaptions Strategies
Derivative traders are usually required to scan through hundreds, even thousands of possible trades on a daily basis.
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