Cover Image

A Comprehensive Study of Implicit and Explicit Biases in Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kazi, Fatima, Young, Alex, Inani, Yash, Rafatirad, Setareh
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Addressing Stereotypes in Large Language Models: A Critical Examination and Mitigation
by: Kazi, Fatima
Published: (2025)

The AI Companion in Education: Analyzing the Pedagogical Potential of ChatGPT in Computer Science and Engineering
by: He, Zhangying, et al.
Published: (2024)

Understanding Intrinsic Socioeconomic Biases in Large Language Models
by: Arzaghi, Mina, et al.
Published: (2024)

Large Language Models are Geographically Biased
by: Manvi, Rohin, et al.
Published: (2024)

A Toolbox for Surfacing Health Equity Harms and Biases in Large Language Models
by: Pfohl, Stephen R., et al.
Published: (2024)

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

Implicit Personalization in Language Models: A Systematic Study
by: Jin, Zhijing, et al.
Published: (2024)

De-Biasing Models of Biased Decisions: A Comparison of Methods Using Mortgage Application Data
by: Tenev, Nicholas
Published: (2024)

Empowering Many, Biasing a Few: Generalist Credit Scoring through Large Language Models
by: Feng, Duanyu, et al.
Published: (2023)

Inducing Human-like Biases in Moral Reasoning Language Models
by: Karpov, Artem, et al.
Published: (2024)

Large-Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season
by: Cen, Sarah H., et al.
Published: (2025)

Subtle Biases Need Subtler Measures: Dual Metrics for Evaluating Representative and Affinity Bias in Large Language Models
by: Kumar, Abhishek, et al.
Published: (2024)

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

ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming
by: Tedeschi, Simone, et al.
Published: (2024)

Measuring and Mitigating Biases in Motor Insurance Pricing
by: Moriah, Mulah, et al.
Published: (2023)

Do Large Language Models Walk Their Talk? Measuring the Gap Between Implicit Associations, Self-Report, and Behavioral Altruism
by: Andric, Sandro
Published: (2025)

You Never Know: Quantization Induces Inconsistent Biases in Vision-Language Foundation Models
by: Slyman, Eric, et al.
Published: (2024)

A Primer on Causal and Statistical Dataset Biases for Fair and Robust Image Analysis
by: Jones, Charles, et al.
Published: (2025)

A Classification of Feedback Loops and Their Relation to Biases in Automated Decision-Making Systems
by: Pagan, Nicolò, et al.
Published: (2023)

Measuring Implicit Bias in Explicitly Unbiased Large Language Models
by: Bai, Xuechunzi, et al.
Published: (2024)

What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices
by: Noels, Sander, et al.
Published: (2025)

LLMSpace: Carbon Footprint Modeling for Large Language Model Inference on LEO Satellites
by: Jiang, Lei, et al.
Published: (2026)

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

Are Models Biased on Text without Gender-related Language?
by: Belém, Catarina G, et al.
Published: (2024)

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

Large Language Model Integrated Healthcare Cyber-Physical Systems Architecture
by: Kankanamge, Malithi Wanniarachchi, et al.
Published: (2024)

Predicting Learning Performance with Large Language Models: A Study in Adult Literacy
by: Zhang, Liang, et al.
Published: (2024)

The Algorithmic Unconscious: Structural Mechanisms and Implicit Biases in Large Language Models
by: Boisnard, Philippe
Published: (2026)

Reward Models Inherit Value Biases from Pretraining
by: Christian, Brian, et al.
Published: (2026)

Humans vs Large Language Models: Judgmental Forecasting in an Era of Advanced AI
by: Abolghasemi, MAhdi, et al.
Published: (2023)

Reducing Biases in Record Matching Through Scores Calibration
by: Moslemi, Mohammad Hossein, et al.
Published: (2024)

Protected group bias and stereotypes in Large Language Models
by: Kotek, Hadas, et al.
Published: (2024)

PropensityBench: Evaluating Latent Safety Risks in Large Language Models via an Agentic Approach
by: Sehwag, Udari Madhushani, et al.
Published: (2025)

Automated Assignment Grading with Large Language Models: Insights From a Bioinformatics Course
by: Poličar, Pavlin G., et al.
Published: (2025)

AI Biases as Asymmetries: A Review to Guide Practice
by: Waters, Gabriella, et al.
Published: (2025)

Moral Sensitivity in LLMs: A Tiered Evaluation of Contextual Bias via Behavioral Profiling and Mechanistic Interpretability
by: Aggarwal, Yash, et al.
Published: (2026)

Limits to Predicting Online Speech Using Large Language Models
by: Remeli, Mina, et al.
Published: (2024)

Revealing Fine-Grained Values and Opinions in Large Language Models
by: Wright, Dustin, et al.
Published: (2024)

SafeCOMM: A Study on Safety Degradation in Fine-Tuned Telecom Large Language Models
by: Djuhera, Aladin, et al.
Published: (2025)

Evaluating LLMs for Demographic-Targeted Social Bias Detection: A Comprehensive Benchmark Study
by: Majumdar, Ayan, et al.
Published: (2025)