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Unlearning Bias in Language Models by Partitioning Gradients
16 references·1 citing·30 second hop
Unlearning Bias in Language Models by Partitioning Gradients (2023)Unlearning Bias in Language Models by Par…Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts (2022)Auto-Debias: Debiasing Masked…Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets (2021)Stereotyping Norwegian Salmon…StereoSet: Measuring stereotypical bias in pretrained language models (2021)StereoSet: Measuring stereoty…Towards Debiasing Sentence Representations (2020)Towards Debiasing Sentence Re…Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection (2020)Null It Out: Guarding Protect…Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020)Language (Technology) is Powe…Investigating Gender Bias in Language Models Using Causal Mediation Analysis (2020)Investigating Gender Bias in …CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models (2020)CrowS-Pairs: A Challenge Data…The Woman Worked as a Babysitter: On Biases in Language Generation (2019)The Woman Worked as a Babysit…On Measuring Social Biases in Sentence Encoders (2019)On Measuring Social Biases in…Measuring Bias in Contextualized Word Representations (2019)Measuring Bias in Contextuali…HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case (2019)HISTORIAE, History of Socio-C…Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Adversarial Removal of Demographic Attributes from Text Data (2018)Adversarial Removal of Demogr…Semantics derived automatically from language corpora contain human-like biases (2017)Semantics derived automatical…Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations (2017)Data Decisions and Theoretica…Social-Group-Agnostic Bias Mitigation via the Stereotype Content Model (2023)Social-Group-Agnostic Bias Mi…Equality of Opportunity in Supervised Learning (2016)Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016)Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Addressing bias in big data and AI for health care: A call for open science (2021)Measuring individual differences in implicit cognition: The implicit association test. (1998)Fairness through awareness (2012)Big Data's Disparate Impact (2014)Dissecting racial bias in an algorithm used to manage the health of populations (2019)A Survey on Bias and Fairness in Machine Learning (2021)ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope (2023)Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Gender bias and stereotypes in Large Language Models (2023)Assessing gender bias in machine translation: a case study with Google Translate (2019)Five sources of bias in natural language processing (2021)Gender and Representation Bias in GPT-3 Generated Stories (2021)Measuring individual differences in implicit cognition: The implicit association test. (1998)Social Biases in NLP Models as Barriers for Persons with Disabilities (2020)Large pre-trained language models contain human-like biases of what is right and wrong to do (2022)Math = male, me = female, therefore math ≠ me. (2002)Biases in Large Language Models: Origins, Inventory, and Discussion (2023)Black Feminist Thought: Knowledge, Consciousness, and the Politics of Empowerment. (1992)Unsettling race and language: Toward a raciolinguistic perspective (2017)Algorithmic Bias in Education (2021)Towards a standard for identifying and managing bias in artificial intelligence (2022)Bias and Fairness in Large Language Models: A Survey (2024)LEGAL-BERT: The Muppets straight out of Law School (2020)On the Opportunities and Risks of Foundation Models (2021)Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologies (2021)Towards trustworthy LLMs: a review on debiasing and dehallucinating in large language models (2024)Auditing large language models: a three-layered approach (2023)
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References

  • 2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case16,511 cited
  • 2017Semantics derived automatically from language corpora contain human-like biases2,845 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2020Language (Technology) is Power: A Critical Survey of “Bias” in NLP1,044 cited
  • 2021StereoSet: Measuring stereotypical bias in pretrained language models643 cited
  • 2019On Measuring Social Biases in Sentence Encoders461 cited
  • 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models438 cited
  • 2019The Woman Worked as a Babysitter: On Biases in Language Generation430 cited
  • 2019Measuring Bias in Contextualized Word Representations348 cited
  • 2020Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection286 cited
  • 2017Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations282 cited
  • 2018Adversarial Removal of Demographic Attributes from Text Data242 cited
  • 2020Towards Debiasing Sentence Representations154 cited
  • 2021Stereotyping Norwegian Salmon: An Inventory of Pitfalls in Fairness Benchmark Datasets143 cited
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Investigating Gender Bias in Language Models Using Causal Mediation Analysis
142 cited
  • 2022Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts119 cited
  • Cited by

    • 2023Social-Group-Agnostic Bias Mitigation via the Stereotype Content Model15 cited