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RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Models ...
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Abstract:
Read paper: https://www.aclanthology.org/2021.acl-long.151 Abstract: Text representation models are prone to exhibit a range of societal biases, reflecting the non-controlled and biased nature of the underlying pretraining data, which consequently leads to severe ethical issues and even bias amplification. Recent work has predominantly focused on measuring and mitigating bias in pretrained language models. Surprisingly, the landscape of bias measurements and mitigation resources and methods for conversational language models is still very scarce: it is limited to only a few types of bias, artificially constructed resources, and completely ignores the impact that debiasing methods may have on the final perfor mance in dialog tasks, e.g., conversational response generation. In this work, we present REDDITBIAS, the first conversational data set grounded in the actual human conversations from Reddit, allowing for bias measurement and mitigation across four important bias dimensions: gender,race,religion, and ...
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Keyword:
Computational Linguistics; Condensed Matter Physics; Deep Learning; Electromagnetism; FOS Physical sciences; Information and Knowledge Engineering; Neural Network; Semantics
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URL: https://underline.io/lecture/25465-redditbias-a-real-world-resource-for-bias-evaluation-and-debiasing-of-conversational-language-models https://dx.doi.org/10.48448/b20r-x634
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How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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Learning Domain-Specialised Representations for Cross-Lingual Biomedical Entity Linking ...
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LexFit: Lexical Fine-Tuning of Pretrained Language Models ...
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A Closer Look at Few-Shot Crosslingual Transfer: The Choice of Shots Matters ...
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Emergent Communication Pretraining for Few-Shot Machine Translation ...
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Manual Clustering and Spatial Arrangement of Verbs for Multilingual Evaluation and Typology Analysis ...
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SemEval-2020 Task 2: Predicting Multilingual and Cross-Lingual (Graded) Lexical Entailment ...
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Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ...
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