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Several recent works have found the emergence of grounded com-positional language in the communication protocols developed bymostly cooperative multi-agent systems when learned end-to-endto maximize performance on a downstream task. However, humanpopulations learn to solve complex tasks involving communicativebehaviors not only in fully cooperative settings but also in scenar-ios where competition acts as an additional external pressure forimprovement. In this work, we investigate whether competitionfor performance from an external, similar agent team could actas a social influence that encourages multi-agent populations todevelop better communication protocols for improved performance,compositionality, and convergence speed. We start fromTask &Talk, a previously proposed referential game betweenmore »
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As natural language processing methods are increasingly deployed in real-world scenarios such as healthcare, legal systems, and social science, it becomes necessary to recognize the role they potentially play in shaping social biases and stereotypes. Previous work has revealed the presence of social biases in widely used word embeddings involving gender, race, religion, and other social constructs. While some methods were proposed to debias these word-level embeddings, there is a need to perform debiasing at the sentence-level given the recent shift towards new contextualized sentence representations such as ELMo and BERT. In this paper, we investigate the presence of socialmore »
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