mlsanityData to 7 Oct 2026

A Comprehensive Survey of Bias in LLMs: Current Landscape and Future Directions

arXiv 2409.16430 ↗First posted 24 Sep 2024cs.CL cs.AI cs.CYcited by 27

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Abstract (arXiv)

Large Language Models(LLMs) have revolutionized various applications in natural language processing (NLP) by providing unprecedented text generation, translation, and comprehension capabilities. However, their widespread deployment has brought to light significant concerns regarding biases embedded within these models. This paper presents a comprehensive survey of biases in LLMs, aiming to provide an extensive review of the types, sources, impacts, and mitigation strategies related to these biases. We systematically categorize biases into several dimensions. Our survey synthesizes current research findings and discusses the implications of biases in real-world applications. Additionally, we critically assess existing bias mitigation techniques and propose future research directions to enhance fairness and equity in LLMs. This survey serves as a foundational resource for researchers, practitioners, and policymakers concerned with addressing and understanding biases in LLMs.

Key facts. Cited by 27 papers in the map (data through 7 Oct 2026). Builds on 28 of its 35 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

28 of 35 references.

References · 28

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2019A Survey on Bias and Fairness in Machine Learningcited by 1,911
  5. 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
  6. 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
  7. 2018Mitigating Unwanted Biases with Adversarial Learningcited by 663
  8. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  9. 2017Fairness in Machine Learning: Lessons from Political Philosophycited by 148
  10. 2023Fairness And Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, And Mitigation Strategiescited by 83
  11. 2024Investigating Bias in LLM-Based Bias Detection: Disparities between LLMs and Human Perceptioncited by 55
  12. 2023Bias Testing and Mitigation in LLM-based Code Generationcited by 53
16 more
  1. 2024Evaluating Gender Bias in Large Language Models via Chain-of-Thought Promptingcited by 49
  2. 2024Measuring Implicit Bias in Explicitly Unbiased Large Language Modelscited by 49
  3. 2024Bias patterns in the application of LLMs for clinical decision support: A comprehensive studycited by 27
  4. 2024(Ir)rationality and Cognitive Biases in Large Language Modelscited by 23
  5. 2024BiasAlert: A Plug-and-play Tool for Social Bias Detection in LLMscited by 21
  6. 2024Breaking Bias, Building Bridges: Evaluation and Mitigation of Social Biases in LLMs via Contact Hypothesiscited by 19
  7. 2023Large Language Model (LLM) Bias Index -- LLMBIcited by 14
  8. 2024Take Care of Your Prompt Bias! Investigating and Mitigating Prompt Bias in Factual Knowledge Extractioncited by 13
  9. 2024PoliTune: Analyzing the Impact of Data Selection and Fine-Tuning on Economic and Political Biases in Large Language Modelscited by 11
  10. 2024Blind Spots and Biases: Exploring the Role of Annotator Cognitive Biases in NLPcited by 11
  11. 2024Comprehensive Study on Sentiment Analysis: From Rule-based to modern LLM based systemcited by 8
  12. 2024Are LLMs Rational Investors? A Study on Detecting and Reducing the Financial Bias in LLMscited by 7
  13. 2024Evaluation of LLMs Biases Towards Elite Universities: A Persona-Based Explorationcited by 7
  14. 2024The Generation Gap: Exploring Age Bias in the Value Systems of Large Language Modelscited by 5
  15. 2024Born With a Silver Spoon? Investigating Socioeconomic Bias in Large Language Modelscited by 4
  16. 2024LangBiTe: A Platform for Testing Bias in Large Language Modelscited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 14; 2026: 13.

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  1. 2025Colombian Waitresses y Jueces canadienses: Gender and Country Biases in Occupation Recommendations from LLMscited by 7
  2. 2025Alignment Revisited: Are Large Language Models Consistent in Stated and Revealed Preferences?cited by 7
  3. 2025Fairness in Agentic AI: A Unified Framework for Ethical and Equitable Multi-Agent Systemcited by 5
  4. 2025Mind the Language Gap: Automated and Augmented Evaluation of Bias in LLMs for High- and Low-Resource Languagescited by 4
  5. 2026Emergently Misaligned Language Models Show Behavioral Self-Awareness That Shifts With Subsequent Realignmentcited by 4
  6. 2025Bias after Prompting: Persistent Discrimination in Large Language Modelscited by 3
  7. 2025Building Trust in Clinical LLMs: Bias Analysis and Dataset Transparencycited by 3
  8. 2025Comprehensive Framework for Evaluating Conversational AI Chatbotscited by 2
  9. 2026CALM: Culturally Self-Aware Language Modelscited by 2
  10. 2026Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detectioncited by 2
  11. 2025Agent-Enhanced Large Language Models for Researching Political Institutionscited by 1
  12. 2025'Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ?cited by 1
15 more
  1. 2026MLLM-as-a-Judge Exhibits Model Preference Biascited by 1
  2. 2025Towards Efficient and Effective Alignment of Large Language Modelscited by 0
  3. 2025A Multi-Agent Probabilistic Inference Framework Inspired by Kairanban-Style CoT System with IdoBata Conversation for Debiasingcited by 0
  4. 2025Audit, Alignment, and Optimization of LM-Powered Subroutines with Application to Public Comment Processingcited by 0
  5. 2025Do They Understand Them? An Updated Evaluation on Nonbinary Pronoun Handling in Large Language Modelscited by 0
  6. 2025A Close Reading Approach to Gender Narrative Biases in AI-Generated Storiescited by 0
  7. 2026The GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultationscited by 0
  8. 2026Measuring Political Stance and Consistency in Large Language Modelscited by 0
  9. 2026Why Do Large Language Models Generate Harmful Content?cited by 0
  10. 2026First, Do No Harm (With LLMs): Mitigating Racial Bias via Agentic Workflowscited by 0
  11. 2026Saying More Than They Know: A Framework for Quantifying Epistemic-Rhetorical Miscalibration in Large Language Modelscited by 0
  12. 2026Fairness-Aware Retrieval Optimization for Retrieval-Augmented Generationcited by 0
  13. 2026Curation of a Cardiology Interface Terminology for Highlighting Electronic Health Records using Machine Learningcited by 0
  14. 2026GAS-Leak-LLM: Genetic Algorithm-Based Suffix Optimization for Black-Box LLM Jailbreakingcited by 0
  15. 2026Wasted large language models: A life cycle thinking approachcited by 0