Copertina

Whose Journey Matters? Investigating Identity Biases in Large Language Models (LLMs) for Travel Planning Assistance

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Ren, Ruiping, Yingwei, Xu, Yao, Xing, Cole, Shu, Wang, Haining
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Artificial Intelligence Computation and Language Computers and Society
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Generative Language Models Exhibit Social Identity Biases
di: Hu, Tiancheng, et al.
Pubblicazione: (2023)

"Pull or Not to Pull?'': Investigating Moral Biases in Leading Large Language Models Across Ethical Dilemmas
di: Ding, Junchen, et al.
Pubblicazione: (2025)

Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
di: Jiang, Han, et al.
Pubblicazione: (2024)

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

The Life Cycle of Large Language Models: A Review of Biases in Education
di: Lee, Jinsook, et al.
Pubblicazione: (2024)

A Systematic Analysis of Biases in Large Language Models
di: Zhang, Xulang, et al.
Pubblicazione: (2025)

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

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

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

Investigating Cultural Alignment of Large Language Models
di: AlKhamissi, Badr, et al.
Pubblicazione: (2024)

Whose Emotions and Moral Sentiments Do Language Models Reflect?
di: He, Zihao, et al.
Pubblicazione: (2024)

PRISM: A Methodology for Auditing Biases in Large Language Models
di: Azzopardi, Leif, et al.
Pubblicazione: (2024)

Indian-BhED: A Dataset for Measuring India-Centric Biases in Large Language Models
di: Khandelwal, Khyati, et al.
Pubblicazione: (2023)

Reinforcement Learning from Human Feedback: Whose Culture, Whose Values, Whose Perspectives?
di: Barman, Kristian González, et al.
Pubblicazione: (2024)

Exploring Possibilities of AI-Powered Legal Assistance in Bangladesh through Large Language Modeling
di: Wasi, Azmine Toushik, et al.
Pubblicazione: (2024)

Urban Computing in the Era of Large Language Models
di: Li, Zhonghang, et al.
Pubblicazione: (2025)

LLMs are Biased Teachers: Evaluating LLM Bias in Personalized Education
di: Weissburg, Iain, et al.
Pubblicazione: (2024)

Large Language Models Develop Novel Social Biases Through Adaptive Exploration
di: Wu, Addison J., et al.
Pubblicazione: (2025)

When AI Speaks, Whose Values Does It Express? A Cross-Cultural Audit of Individualism-Collectivism Bias in Large Language Models
di: Venkata, Pruthvinath Jeripity
Pubblicazione: (2026)

Temporal Preferences in Language Models for Long-Horizon Assistance
di: Mazyaki, Ali, et al.
Pubblicazione: (2025)

Is Self-knowledge and Action Consistent or Not: Investigating Large Language Model's Personality
di: Ai, Yiming, et al.
Pubblicazione: (2024)

Robust Pronoun Fidelity with English LLMs: Are they Reasoning, Repeating, or Just Biased?
di: Gautam, Vagrant, et al.
Pubblicazione: (2024)

Self-Blinding and Counterfactual Self-Simulation Mitigate Biases and Sycophancy in Large Language Models
di: Christian, Brian, et al.
Pubblicazione: (2026)

"Whose Side Are You On?" Estimating Ideology of Political and News Content Using Large Language Models and Few-shot Demonstration Selection
di: Haroon, Muhammad, et al.
Pubblicazione: (2025)

Whose Personae? Synthetic Persona Experiments in LLM Research and Pathways to Transparency
di: Batzner, Jan, et al.
Pubblicazione: (2025)

MEDEQUALQA: Evaluating Biases in LLMs with Counterfactual Reasoning
di: Ghosh, Rajarshi, et al.
Pubblicazione: (2025)

Investigating Political and Demographic Associations in Large Language Models Through Moral Foundations Theory
di: Smith-Vaniz, Nicole, et al.
Pubblicazione: (2025)

Language of Thought Shapes Output Diversity in Large Language Models
di: Xu, Shaoyang, et al.
Pubblicazione: (2026)

How Large Language Models (LLMs) Extrapolate: From Guided Missiles to Guided Prompts
di: Cao, Xuenan
Pubblicazione: (2024)

Decoding the Mind of Large Language Models: A Quantitative Evaluation of Ideology and Biases
di: Hirose, Manari, et al.
Pubblicazione: (2025)

PRIDE -- Parameter-Efficient Reduction of Identity Discrimination for Equality in LLMs
di: Menke, Maluna, et al.
Pubblicazione: (2025)

Revealing and Reducing Gender Biases in Vision and Language Assistants (VLAs)
di: Girrbach, Leander, et al.
Pubblicazione: (2024)

Large Language Models (LLMs) as Agents for Augmented Democracy
di: Gudiño-Rosero, Jairo, et al.
Pubblicazione: (2024)

The "Colonial Impulse" of Natural Language Processing: An Audit of Bengali Sentiment Analysis Tools and Their Identity-based Biases
di: Das, Dipto, et al.
Pubblicazione: (2024)

White Men Lead, Black Women Help? Benchmarking and Mitigating Language Agency Social Biases in LLMs
di: Wan, Yixin, et al.
Pubblicazione: (2024)

Measuring What Matters -- or What's Convenient?: Robustness of LLM-Based Scoring Systems to Construct-Irrelevant Factors
di: Walsh, Cole, et al.
Pubblicazione: (2026)

Why are all LLMs Obsessed with Japanese Culture? On the Hidden Cultural and Regional Biases of LLMs
di: de Landa, Joseba Fernandez, et al.
Pubblicazione: (2026)

Large Language Models Show Human-like Social Desirability Biases in Survey Responses
di: Salecha, Aadesh, et al.
Pubblicazione: (2024)

CDEval: A Benchmark for Measuring the Cultural Dimensions of Large Language Models
di: Wang, Yuhang, et al.
Pubblicazione: (2023)

An Investigation into Misuse of Java Security APIs by Large Language Models
di: Mousavi, Zahra, et al.
Pubblicazione: (2024)