Cover Image

Datasets for Fairness in Language Models: An In-Depth Survey

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Zhang, Jiale, Wang, Zichong, Palikhe, Avash, Yin, Zhipeng, Zhang, Wenbin
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Computers and Society Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fairness Definitions in Language Models Explained
by: Yin, Zhipeng, et al.
Published: (2024)

Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AI
by: Amon, Archer, et al.
Published: (2024)

Towards Transparent AI: A Survey on Explainable Large Language Models
by: Palikhe, Avash, et al.
Published: (2025)

Towards Transparent AI: A Survey on Explainable Language Models
by: Palikhe, Avash, et al.
Published: (2025)

AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Models
by: Yin, Zhipeng, et al.
Published: (2025)

AI Fairness Beyond Complete Demographics: Current Achievements and Future Directions
by: Wang, Zichong, et al.
Published: (2025)

Fairness-Aware Graph Representation Learning with Limited Demographic Information
by: Wang, Zichong, et al.
Published: (2025)

Generative AI in Depth: A Survey of Recent Advances, Model Variants, and Real-World Applications
by: Yazdani, Shamim, et al.
Published: (2025)

Fairness in Large Language Models in Three Hours
by: Viet, Thang Doan, et al.
Published: (2024)

Bias and Fairness in Large Language Models: A Survey
by: Gallegos, Isabel O., et al.
Published: (2023)

Fairness in Large Language Models: A Taxonomic Survey
by: Chu, Zhibo, et al.
Published: (2024)

Exploring Accuracy-Fairness Trade-off in Large Language Models
by: Zhang, Qingquan, et al.
Published: (2024)

Harnessing Large Language Models for Disaster Management: A Survey
by: Lei, Zhenyu, et al.
Published: (2025)

Towards Large Language Models that Benefit for All: Benchmarking Group Fairness in Reward Models
by: Song, Kefan, et al.
Published: (2025)

FairPair: A Robust Evaluation of Biases in Language Models through Paired Perturbations
by: Dwivedi-Yu, Jane, et al.
Published: (2024)

Intrinsic Meets Extrinsic Fairness: Assessing the Downstream Impact of Bias Mitigation in Large Language Models
by: Arzaghi', 'Mina, et al.
Published: (2025)

Fairness of ChatGPT
by: Li, Yunqi, et al.
Published: (2023)

LangFair: A Python Package for Assessing Bias and Fairness in Large Language Model Use Cases
by: Bouchard, Dylan, et al.
Published: (2025)

Balancing the Scales: Reinforcement Learning for Fair Classification
by: Eshuijs, Leon, et al.
Published: (2024)

Addressing Both Statistical and Causal Gender Fairness in NLP Models
by: Chen, Hannah, et al.
Published: (2024)

Humanizing LLMs: A Survey of Psychological Measurements with Tools, Datasets, and Human-Agent Applications
by: Dong, Wenhan, et al.
Published: (2025)

Laissez-Faire Harms: Algorithmic Biases in Generative Language Models
by: Shieh, Evan, et al.
Published: (2024)

Siren's Song in the AI Ocean: A Survey on Hallucination in Large Language Models
by: Zhang, Yue, et al.
Published: (2023)

Surveying Attitudinal Alignment Between Large Language Models Vs. Humans Towards 17 Sustainable Development Goals
by: Wu, Qingyang, et al.
Published: (2024)

Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
by: Xian, Ruicheng, et al.
Published: (2025)

AXOLOTL: Fairness through Assisted Self-Debiasing of Large Language Model Outputs
by: Ebrahimi, Sana, et al.
Published: (2024)

RedTopic: Toward Topic-Diverse Red Teaming of Large Language Models
by: Ding, Jiale, et al.
Published: (2025)

Unmasking and Improving Data Credibility: A Study with Datasets for Training Harmless Language Models
by: Zhu, Zhaowei, et al.
Published: (2023)

ELMES: An Automated Framework for Evaluating Large Language Models in Educational Scenarios
by: Wei, Shou'ang, et al.
Published: (2025)

Fair Representation in Parliamentary Summaries: Measuring and Mitigating Inclusion Bias
by: Cunningham, Eoghan, et al.
Published: (2025)

Strategic Demonstration Selection for Improved Fairness in LLM In-Context Learning
by: Hu, Jingyu, et al.
Published: (2024)

Exploring Consciousness in LLMs: A Systematic Survey of Theories, Implementations, and Frontier Risks
by: Chen, Sirui, et al.
Published: (2025)

Are Large Language Models Chameleons? An Attempt to Simulate Social Surveys
by: Geng, Mingmeng, et al.
Published: (2024)

LLM-Assisted Content Conditional Debiasing for Fair Text Embedding
by: Deng, Wenlong, et al.
Published: (2024)

BadFair: Backdoored Fairness Attacks with Group-conditioned Triggers
by: Xue, Jiaqi, et al.
Published: (2024)

ResumeAtlas: Revisiting Resume Classification with Large-Scale Datasets and Large Language Models
by: Heakl, Ahmed, et al.
Published: (2024)

Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs
by: Hartmann, David, et al.
Published: (2026)

Towards Modeling Learner Performance with Large Language Models
by: Neshaei, Seyed Parsa, et al.
Published: (2024)

Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey
by: Deng, Chengyuan, et al.
Published: (2024)

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches
by: Azime, Israel Abebe, et al.
Published: (2025)