Before revision:  We specifically compare responses to Twitter posts about marginalized communities (#BlackLivesMatter, #MeToo) and other topics (#Vegan, #WFH)  . Furthermore, we propose a constrained decoding technique that uses salient n-gram similarity to apply soft constraints to top-k sampling and can decrease the amount of ad hominems generated by dialogue systems .
After revision:  We specifically compare responses to Twitter posts about marginalized communities (#BlackLivesMatter, #MeToo) and other topics (#Vegan, #WFH) , because the abusive language of ad hominems could further amplify the skew of power away from marginalized populations . Furthermore, we propose a constrained decoding technique that uses salient n-gram similarity to apply soft constraints to top-k sampling and can decrease the amount of ad hominems generated by dialogue systems .