mlsanityData to 7 Oct 2026

What an Elegant Bridge: Multilingual LLMs are Biased Similarly in Different Languages

arXiv 2407.09704 ↗First posted 12 Jul 2024cs.CLcited by 5

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Abstract (arXiv)

This paper investigates biases of Large Language Models (LLMs) through the lens of grammatical gender. Drawing inspiration from seminal works in psycholinguistics, particularly the study of gender's influence on language perception, we leverage multilingual LLMs to revisit and expand upon the foundational experiments of Boroditsky (2003). Employing LLMs as a novel method for examining psycholinguistic biases related to grammatical gender, we prompt a model to describe nouns with adjectives in various languages, focusing specifically on languages with grammatical gender. In particular, we look at adjective co-occurrences across gender and languages, and train a binary classifier to predict grammatical gender given adjectives an LLM uses to describe a noun. Surprisingly, we find that a simple classifier can not only predict noun gender above chance but also exhibit cross-language transferability. We show that while LLMs may describe words differently in different languages, they are biased similarly.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 15 of its 34 references that are in the map. First posted on arXiv 12 Jul 2024.

Builds on

15 of 34 references.

References · 15

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  2. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  3. 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
  4. 2023A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivitycited by 888
  5. 2023How Good Are GPT Models at Machine Translation? A Comprehensive Evaluationcited by 344
  6. 2023MEGA: Multilingual Evaluation of Generative AIcited by 291
  7. 2019Evaluating Gender Bias in Machine Translationcited by 247
  8. 2018Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systemscited by 234
  9. 2021Bias Out-of-the-Box: An Empirical Analysis of Intersectional Occupational Biases in Popular Generative Language Modelscited by 141
  10. 2019Getting Gender Right in Neural Machine Translationcited by 98
  11. 2019Evaluating the Underlying Gender Bias in Contextualized Word Embeddingscited by 94
  12. 2023VisoGender: A dataset for benchmarking gender bias in image-text pronoun resolutioncited by 52
3 more
  1. 2023Global Voices, Local Biases: Socio-Cultural Prejudices across Languagescited by 23
  2. 2020On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbscited by 8
  3. 2019Grammatical Gender, Neo-Whorfianism, and Word Embeddings: A Data-Driven Approach to Linguistic Relativitycited by 2

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025Deterministic or probabilistic? The psychology of LLMs as random number generatorscited by 6
  2. 2025Assessing Agentic Large Language Models in Multilingual National Biascited by 0
  3. 2026Benchmarking Concept-Spilling Across Languages in LLMscited by 0
  4. 2026MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generationcited by 0
  5. 2026Estimating Grammatical Gender Directions in Contextual Embeddings under Controlled and Natural Contextscited by 0