Identifying and Reducing Gender Bias in Word-Level Language Models
Table 8: CNN/Daily Mail bias scores for the words biased towards female gender for different λ values
['[BOLD] Target Words', '[ITALIC] training', '[ITALIC] λ=0.0', '[ITALIC] λ=0.1', '[ITALIC] λ=0.5', '[ITALIC] λ=0.8', '[ITALIC] λ=1.0']
The tables show how the scores vary for the training text and the generated text for different values of λ