Image de couverture de livre

Assessing Gender Bias in LLMs: Comparing LLM Outputs with Human Perceptions and Official Statistics

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteur principal:	Bas, Tetiana
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias
par: Chen, Yuen, et autres
Publié: (2022)

The Confidence Trap: Gender Bias and Predictive Certainty in LLMs
par: Sabir, Ahmed, et autres
Publié: (2026)

Relative Bias: A Comparative Framework for Quantifying Bias in LLMs
par: Arbabi, Alireza, et autres
Publié: (2025)

Detecting Gender Bias in Course Evaluations
par: Lindau, Sarah, et autres
Publié: (2024)

Mitigating Gender Bias in Contextual Word Embeddings
par: Yarrabelly, Navya, et autres
Publié: (2024)

Extracting Prompts by Inverting LLM Outputs
par: Zhang, Collin, et autres
Publié: (2024)

Understanding Gender Bias in AI-Generated Product Descriptions
par: Kelly, Markelle, et autres
Publié: (2025)

Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
par: Vargas, Francisco, et autres
Publié: (2020)

Assessing LLM Text Detection in Educational Contexts: Does Human Contribution Affect Detection?
par: Gehring, Lukas, et autres
Publié: (2025)

Dementia Through Different Eyes: Explainable Modeling of Human and LLM Perceptions for Early Awareness
par: Peled-Cohen, Lotem, et autres
Publié: (2025)

GG-BBQ: German Gender Bias Benchmark for Question Answering
par: Satheesh, Shalaka, et autres
Publié: (2025)

Exploring Gender Bias in Large Language Models: An In-depth Dive into the German Language
par: Gnadt, Kristin, et autres
Publié: (2025)

A Comparative Analysis of LLM Memorization at Statistical and Internal Levels: Cross-Model Commonalities and Model-Specific Signatures
par: Chen, Bowen, et autres
Publié: (2026)

Real-Time Trustworthiness Scoring for LLM Structured Outputs and Data Extraction
par: Goh, Hui Wen, et autres
Publié: (2026)

Bridging Human and Model Perspectives: A Comparative Analysis of Political Bias Detection in News Media Using Large Language Models
par: Banik, Shreya Adrita, et autres
Publié: (2025)

Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs
par: Su, Guinan, et autres
Publié: (2026)

Addressing Both Statistical and Causal Gender Fairness in NLP Models
par: Chen, Hannah, et autres
Publié: (2024)

Mitigating Extrinsic Gender Bias for Bangla Classification Tasks
par: Joy, Sajib Kumar Saha, et autres
Publié: (2024)

Explaining Length Bias in LLM-Based Preference Evaluations
par: Hu, Zhengyu, et autres
Publié: (2024)

CAOTE: KV Cache Selection for LLMs via Attention Output Error-Based Token Eviction
par: Goel, Raghavv, et autres
Publié: (2025)

Output Embedding Centering for Stable LLM Pretraining
par: Stollenwerk, Felix, et autres
Publié: (2026)

Localizing Malicious Outputs from CodeLLM
par: Borana, Mayukh, et autres
Publié: (2025)

Profiling News Media for Factuality and Bias Using LLMs and the Fact-Checking Methodology of Human Experts
par: Mujahid, Zain Muhammad, et autres
Publié: (2025)

Format as a Prior: Quantifying and Analyzing Bias in LLMs for Heterogeneous Data
par: Liu, Jiacheng, et autres
Publié: (2025)

A Fast and Effective Solution to the Problem of Look-ahead Bias in LLMs
par: Merchant, Humzah, et autres
Publié: (2025)

Sustainable LLM Inference for Edge AI: Evaluating Quantized LLMs for Energy Efficiency, Output Accuracy, and Inference Latency
par: Husom, Erik Johannes, et autres
Publié: (2025)

The Impact of Inference Acceleration on Bias of LLMs
par: Kirsten, Elisabeth, et autres
Publié: (2024)

Exploring Changes in Nation Perception with Nationality-Assigned Personas in LLMs
par: Kamruzzaman, Mahammed, et autres
Publié: (2024)

Bias patterns in the application of LLMs for clinical decision support: A comprehensive study
par: Poulain, Raphael, et autres
Publié: (2024)

Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation
par: Miandoab, Kaveh Eskandari, et autres
Publié: (2025)

Gender Bias in Instruction-Guided Speech Synthesis Models
par: Kuan, Chun-Yi, et autres
Publié: (2025)

MoESD: Mixture of Experts Stable Diffusion to Mitigate Gender Bias
par: Wang, Guorun, et autres
Publié: (2024)

Gender Bias in Explainability: Investigating Performance Disparity in Post-hoc Methods
par: Dhaini, Mahdi, et autres
Publié: (2025)

Breaking Language Barriers or Reinforcing Bias? A Study of Gender and Racial Disparities in Multilingual Contrastive Vision Language Models
par: Sahili, Zahraa Al, et autres
Publié: (2025)

Bias in LLMs as Annotators: The Effect of Party Cues on Labelling Decision by Large Language Models
par: Vera, Sebastian Vallejo, et autres
Publié: (2024)

Benchmarking Gender and Political Bias in Large Language Models
par: Yang, Jinrui, et autres
Publié: (2025)

Aligning LLMs with Human Uncertainty: A Beta-Bernoulli Calibrator for LLM Forecasting
par: Dai, Hui, et autres
Publié: (2026)

Beyond Early-Token Bias: Model-Specific and Language-Specific Position Effects in Multilingual LLMs
par: Menschikov, Mikhail, et autres
Publié: (2025)

Intrinsic Meets Extrinsic Fairness: Assessing the Downstream Impact of Bias Mitigation in Large Language Models
par: Arzaghi', 'Mina, et autres
Publié: (2025)

SafetyNet: Detecting Harmful Outputs in LLMs by Modeling and Monitoring Deceptive Behaviors
par: Chaudhary, Maheep, et autres
Publié: (2025)