mlsanityData to 7 Oct 2026

Socially Aware Bias Measurements for Hindi Language Representations

arXiv 2110.07871 ↗First posted 15 Oct 2021cs.CLcited by 29

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Abstract (arXiv)

Language representations are efficient tools used across NLP applications, but they are strife with encoded societal biases. These biases are studied extensively, but with a primary focus on English language representations and biases common in the context of Western society. In this work, we investigate biases present in Hindi language representations with focuses on caste and religion-associated biases. We demonstrate how biases are unique to specific language representations based on the history and culture of the region they are widely spoken in, and how the same societal bias (such as binary gender-associated biases) is encoded by different words and text spans across languages. The discoveries of our work highlight the necessity of culture awareness and linguistic artifacts when modeling language representations, in order to better understand the encoded biases.

Key facts. Cited by 29 papers in the map (data through 7 Oct 2026). Builds on 20 of its 42 references that are in the map. First posted on arXiv 15 Oct 2021.

Builds on

20 of 42 references.

References · 20

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2016Enriching Word Vectors with Subword Informationcited by 1,578
  3. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  4. 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
  5. 2020CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Modelscited by 703
  6. 2019On Measuring Social Biases in Sentence Encoderscited by 397
  7. 2019Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddingscited by 146
  8. 2021Harms of Gender Exclusivity and Challenges in Non-Binary Representation in Language Technologiescited by 128
  9. 2017The IIT Bombay English-Hindi Parallel Corpuscited by 74
  10. 2019Attenuating Bias in Word Vectorscited by 64
  11. 2020Gender Bias in Multilingual Embeddings and Cross-Lingual Transfercited by 55
  12. 2019Plan, Write, and Revise: an Interactive System for Open-Domain Story Generationcited by 43
8 more
  1. 2019Examining Gender Bias in Languages with Grammatical Gendercited by 40
  2. 2020OSCaR: Orthogonal Subspace Correction and Rectification of Biases in Word Embeddingscited by 40
  3. 2021Detecting Cross-Geographic Biases in Toxicity Modeling on Social Mediacited by 31
  4. 2020AraWEAT: Multidimensional Analysis of Biases in Arabic Word Embeddingscited by 20
  5. 2020Evaluating Bias In Dutch Word Embeddingscited by 15
  6. 2020Non-portability of Algorithmic Fairness in Indiacited by 7
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  8. 2021Gender Bias, Social Bias and Representation: 70 Years of BHollywoodcited by 4

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 6; 2023: 11; 2024: 7; 2025: 3; 2026: 2.

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  1. 2023Bias and Fairness in Large Language Models: A Surveycited by 626
  2. 2023Evaluating the Social Impact of Generative AI Systems in Systems and Societycited by 91
  3. 2022Re-contextualizing Fairness in NLP: The Case of Indiacited by 55
  4. 2023Comparing Biases and the Impact of Multilingual Training across Multiple Languagescited by 36
  5. 2024IndiBias: A Benchmark Dataset to Measure Social Biases in Language Models for Indian Contextcited by 32
  6. 2023Sociodemographic Bias in Language Models: A Survey and Forward Pathcited by 27
  7. 2024Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Artcited by 26
  8. 2023Building Socio-culturally Inclusive Stereotype Resources with Community Engagementcited by 25
  9. 2024SeeGULL Multilingual: a Dataset of Geo-Culturally Situated Stereotypescited by 24
  10. 2022Under the Morphosyntactic Lens: A Multifaceted Evaluation of Gender Bias in Speech Translationcited by 23
  11. 2023Global Voices, Local Biases: Socio-Cultural Prejudices across Languagescited by 23
  12. 2023Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Modelscited by 17
17 more
  1. 2023Evaluating Gender Bias of Pre-trained Language Models in Natural Language Inference by Considering All Labelscited by 16
  2. 2024Do Multilingual Large Language Models Mitigate Stereotype Bias?cited by 13
  3. 2025DECASTE: Unveiling Caste Stereotypes in Large Language Models through Multi-Dimensional Bias Analysiscited by 12
  4. 2023Tackling Bias in Pre-trained Language Models: Current Trends and Under-represented Societiescited by 11
  5. 2022Mitigating Gender Stereotypes in Hindi and Marathicited by 6
  6. 2024Hire Me or Not? Examining Language Model's Behavior with Occupation Attributescited by 5
  7. 2025Measuring What Matters: Connecting AI Ethics Evaluations to System Attributes, Hazards, and Harmscited by 5
  8. 2022Cultural Re-contextualization of Fairness Research in Language Technologies in Indiacited by 4
  9. 2022Undesirable Biases in NLP: Addressing Challenges of Measurementcited by 4
  10. 2024An Empirical Study on the Characteristics of Bias upon Context Length Variation for Banglacited by 4
  11. 2022Efficient Gender Debiasing of Pre-trained Indic Language Modelscited by 3
  12. 2023When your Cousin has the Right Connections: Unsupervised Bilingual Lexicon Induction for Related Data-Imbalanced Languagescited by 3
  13. 2023In What Languages are Generative Language Models the Most Formal? Analyzing Formality Distribution across Languagescited by 2
  14. 2024Impoverished Language Technology: The Lack of (Social) Class in NLPcited by 1
  15. 2025Social Bias in Multilingual Language Models: A Surveycited by 1
  16. 2026AmchiBias: Measuring Stereotypical Bias in Goan Identity Groups with a Minimal Pair Dataset in English and Konkanicited by 1
  17. 2026Safety Alignment Illusion: The Cross-Lingual Safety Gap in LLMscited by 0