REDUCING BIAS IN SENTIMENT ANALYSIS MODELS THROUGH CAUSAL MEDIATION ANALYSIS AND TARGETED COUNTERFACTUAL TRAINING

Reducing Bias in Sentiment Analysis Models Through Causal Mediation Analysis and Targeted Counterfactual Training

Large language models provide high-accuracy solutions in many natural language processing tasks.In particular, they are used as word embeddings in sentiment analysis models.However, these models pick up on and amplify biases and social stereotypes in the data.Causality theory has recently driven the development of effective algorithms to evaluate a

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A Gas Path Fault Contribution Matrix for Marine Gas Turbine Diagnosis Based on a Multiple Model Fault Detection and Isolation Approach

To ensure reliable and efficient operation of gas turbines, multiple model (MM) approaches have been extensively studied for online fault detection and isolation (FDI).However, current MM-FDI approaches are difficult to directly apply to gas path FDI, which is one click here of the common faults in gas turbines and is understood to mainly be due to

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