mlsanityData to 7 Oct 2026

Cultural Re-contextualization of Fairness Research in Language Technologies in India

arXiv 2211.11206 ↗First posted 21 Nov 2022cs.CL cs.AI cs.CYcited by 4

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Abstract (arXiv)

Recent research has revealed undesirable biases in NLP data and models. However, these efforts largely focus on social disparities in the West, and are not directly portable to other geo-cultural contexts. In this position paper, we outline a holistic research agenda to re-contextualize NLP fairness research for the Indian context, accounting for Indian societal context, bridging technological gaps in capability and resources, and adapting to Indian cultural values. We also summarize findings from an empirical study on various social biases along different axes of disparities relevant to India, demonstrating their prevalence in corpora and models.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 14 of its 20 references that are in the map. First posted on arXiv 21 Nov 2022.

Builds on

14 of 20 references.

References · 14

  1. 2021On the Opportunities and Risks of Foundation Modelscited by 3,961
  2. 2020Language (Technology) is Power: A Critical Survey of "Bias" in NLPcited by 951
  3. 2021Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpuscited by 481
  4. 2020Artificial Intelligence, Values and Alignmentcited by 443
  5. 2020Measuring and Reducing Gendered Correlations in Pre-trained Modelscited by 222
  6. 2021MuRIL: Multilingual Representations for Indian Languagescited by 177
  7. 2020Participatory Research for Low-resourced Machine Translation: A Case Study in African Languagescited by 159
  8. 2021Re-imagining Algorithmic Fairness in India and Beyondcited by 102
  9. 2019Perturbation Sensitivity Analysis to Detect Unintended Model Biasescited by 74
  10. 2022Re-contextualizing Fairness in NLP: The Case of Indiacited by 55
  11. 2022Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selectioncited by 52
  12. 2021Whose Ground Truth? Accounting for Individual and Collective Identities Underlying Dataset Annotationcited by 51
2 more
  1. 2021Socially Aware Bias Measurements for Hindi Language Representationscited by 29
  2. 2022A Human Rights-Based Approach to Responsible AIcited by 20

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 0; 2025: 2; 2026: 1.

4 papers.

  1. 2023Scaling Laws Do Not Scalecited by 13
  2. 2025DRISHTIKON: A Multimodal Multilingual Benchmark for Testing Language Models' Understanding on Indian Culturecited by 13
  3. 2025FairI Tales: Evaluation of Fairness in Indian Contexts with a Focus on Bias and Stereotypescited by 9
  4. 2026Safety Alignment Illusion: The Cross-Lingual Safety Gap in LLMscited by 0