Buchumschlag

"You Gotta be a Doctor, Lin": An Investigation of Name-Based Bias of Large Language Models in Employment Recommendations

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Nghiem, Huy, Prindle, John, Zhao, Jieyu, Daumé III, Hal
Format:	Preprint
Veröffentlicht:	2024
Schlagworte:	Artificial Intelligence Computation and Language
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Models
von: Nghiem, Huy, et al.
Veröffentlicht: (2024)

SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Models
von: Nghiem, Huy, et al.
Veröffentlicht: (2025)

Bias in the Tails: How Name-conditioned Evaluative Framing in Resume Summaries Destabilizes LLM-based Hiring
von: Nghiem, Huy, et al.
Veröffentlicht: (2026)

'Rich Dad, Poor Lad': How do Large Language Models Contextualize Socioeconomic Factors in College Admission ?
von: Nghiem, Huy, et al.
Veröffentlicht: (2025)

A Necessary Step toward Faithfulness: Measuring and Improving Consistency in Free-Text Explanations
von: Zhao, Lingjun, et al.
Veröffentlicht: (2025)

Balancing Safety and Helpfulness in Healthcare AI Assistants through Iterative Preference Alignment
von: Nghiem, Huy, et al.
Veröffentlicht: (2025)

Language Models Predict Empathy Gaps Between Social In-groups and Out-groups
von: Hou, Yu, et al.
Veröffentlicht: (2025)

Steering Safely or Off a Cliff? Rethinking Specificity and Robustness in Inference-Time Interventions
von: Goyal, Navita, et al.
Veröffentlicht: (2026)

Successfully Guiding Humans with Imperfect Instructions by Highlighting Potential Errors and Suggesting Corrections
von: Zhao, Lingjun, et al.
Veröffentlicht: (2024)

Do great minds think alike? Investigating Human-AI Complementarity in Question Answering with CAIMIRA
von: Gor, Maharshi, et al.
Veröffentlicht: (2024)

Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style
von: Baumler, Connor, et al.
Veröffentlicht: (2026)

Pragmatics Meets Culture: Culturally-adapted Artwork Description Generation and Evaluation
von: Zhao, Lingjun, et al.
Veröffentlicht: (2026)

Can Hallucination Correction Improve Video-Language Alignment?
von: Zhao, Lingjun, et al.
Veröffentlicht: (2025)

When Stereotypes GTG: The Impact of Predictive Text Suggestions on Gender Bias in Human-AI Co-Writing
von: Baumler, Connor, et al.
Veröffentlicht: (2024)

Reheat Nachos for Dinner? Evaluating AI Support for Cross-Cultural Communication of Neologisms
von: Ki, Dayeon, et al.
Veröffentlicht: (2026)

Toxicity Detection is NOT all you Need: Measuring the Gaps to Supporting Volunteer Content Moderators
von: Cao, Yang Trista, et al.
Veröffentlicht: (2023)

Investigating Intersectional Bias in Large Language Models using Confidence Disparities in Coreference Resolution
von: Khan, Falaah Arif, et al.
Veröffentlicht: (2025)

A System for Name and Address Parsing with Large Language Models
von: Tarannum, Adeeba, et al.
Veröffentlicht: (2026)

Safer-Instruct: Aligning Language Models with Automated Preference Data
von: Shi, Taiwei, et al.
Veröffentlicht: (2023)

TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
von: Zheng, Ruijie, et al.
Veröffentlicht: (2023)

The Impact of Explanations on Fairness in Human-AI Decision-Making: Protected vs Proxy Features
von: Goyal, Navita, et al.
Veröffentlicht: (2023)

What's in a Name? Auditing Large Language Models for Race and Gender Bias
von: Salinas, Alejandro, et al.
Veröffentlicht: (2024)

SparseDoctor: Towards Efficient Chat Doctor with Mixture of Experts Enhanced Large Language Models
von: Zhang, Jianbin, et al.
Veröffentlicht: (2025)

LLM-DER:A Named Entity Recognition Method Based on Large Language Models for Chinese Coal Chemical Domain
von: Xiao, Le, et al.
Veröffentlicht: (2024)

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation
von: Luo, Guoqing, et al.
Veröffentlicht: (2025)

Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs
von: Kumar, Divyanshu, et al.
Veröffentlicht: (2024)

Harnessing Large Language Models for Biomedical Named Entity Recognition
von: Chen, Jian, et al.
Veröffentlicht: (2025)

Investigating Annotator Bias in Large Language Models for Hate Speech Detection
von: Das, Amit, et al.
Veröffentlicht: (2024)

TRIZ-RAGNER: A Retrieval-Augmented Large Language Model for TRIZ-Aware Named Entity Recognition in Patent-Based Contradiction Mining
von: Xu, Zitong, et al.
Veröffentlicht: (2026)

Regional Bias in Large Language Models
von: Gopinadh, M P V S, et al.
Veröffentlicht: (2026)

A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges
von: Li, Zongxia, et al.
Veröffentlicht: (2025)

Self-Preference Bias in Rubric-Based Evaluation of Large Language Models
von: Pombal, José, et al.
Veröffentlicht: (2026)

Leveraging Large Language Models for Rare Disease Named Entity Recognition
von: Xi, Nan Miles, et al.
Veröffentlicht: (2025)

Whose Side Are You On? Investigating the Political Stance of Large Language Models
von: Pit, Pagnarasmey, et al.
Veröffentlicht: (2024)

The Unequal Opportunities of Large Language Models: Revealing Demographic Bias through Job Recommendations
von: Salinas, Abel, et al.
Veröffentlicht: (2023)

Born With a Silver Spoon? Investigating Socioeconomic Bias in Large Language Models
von: Singh, Smriti, et al.
Veröffentlicht: (2024)

Large Language Models Are Still Misled by Simple Bias Ensembles
von: Sun, Zhouhao, et al.
Veröffentlicht: (2025)

Towards Efficient Large Language Models for Scientific Text: A Review
von: To, Huy Quoc, et al.
Veröffentlicht: (2024)

Does Differential Privacy Impact Bias in Pretrained NLP Models?
von: Islam, Md. Khairul, et al.
Veröffentlicht: (2024)

Assessing Political Bias in Large Language Models
von: Rettenberger, Luca, et al.
Veröffentlicht: (2024)