Cover Image

The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Rios-Sialer, Ian
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Computation and Language Computers and Society
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Building Trust: Foundations of Security, Safety and Transparency in AI
by: Sidhpurwala, Huzaifa, et al.
Published: (2024)

Towards Meaningful Transparency in Civic AI Systems
by: Murray-Rust, Dave, et al.
Published: (2025)

EtiCor++: Towards Understanding Etiquettical Bias in LLMs
by: Dwivedi, Ashutosh, et al.
Published: (2025)

Towards Measuring and Modeling "Culture" in LLMs: A Survey
by: Adilazuarda, Muhammad Farid, et al.
Published: (2024)

We're Different, We're the Same: Creative Homogeneity Across LLMs
by: Wenger, Emily, et al.
Published: (2025)

From Hard Refusals to Safe-Completions: Toward Output-Centric Safety Training
by: Yuan, Yuan, et al.
Published: (2025)

Towards Safe Multilingual Frontier AI
by: Kanepajs, Artūrs, et al.
Published: (2024)

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

The Double Contingency Problem: AI Recursion and the Limits of Interspecies Understanding
by: Bishop, Graham L.
Published: (2025)

Towards medical AI misalignment: a preliminary study
by: Puccio, Barbara, et al.
Published: (2025)

Knowledge Acquisition on Mass-shooting Events via LLMs for AI-Driven Justice
by: Ihugba, Benign John, et al.
Published: (2025)

Safetywashing: Do AI Safety Benchmarks Actually Measure Safety Progress?
by: Ren, Richard, et al.
Published: (2024)

From Rogue to Safe AI: The Role of Explicit Refusals in Aligning LLMs with International Humanitarian Law
by: Mavi, John, et al.
Published: (2025)

Rethinking Test-Time Scaling for Medical AI: Model and Task-Aware Strategies for LLMs and VLMs
by: Oh, Gyutaek, et al.
Published: (2025)

Mitigating Gambling-Like Risk-Taking Behaviors in Large Language Models: A Behavioral Economics Approach to AI Safety
by: Du, Y.
Published: (2025)

Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction
by: Li, Ming, et al.
Published: (2025)

Guided Persona-based AI Surveys: Can we replicate personal mobility preferences at scale using LLMs?
by: Tzachristas, Ioannis, et al.
Published: (2025)

Medical Malice: A Dataset for Context-Aware Safety in Healthcare LLMs
by: D'addario, Andrew Maranhão Ventura
Published: (2025)

AI Act and Large Language Models (LLMs): When critical issues and privacy impact require human and ethical oversight
by: Fabiano, Nicola
Published: (2024)

Questionnaire Responses Do not Capture the Safety of AI Agents
by: Hellrigel-Holderbaum, Max, et al.
Published: (2026)

When Style Breaks Safety: Defending LLMs Against Superficial Style Alignment
by: Xiao, Yuxin, et al.
Published: (2025)

Assessing the Performance of Human-Capable LLMs -- Are LLMs Coming for Your Job?
by: Mavi, John, et al.
Published: (2024)

Evaluating Psychological Safety of Large Language Models
by: Li, Xingxuan, et al.
Published: (2022)

The simulation of judgment in LLMs
by: Loru, Edoardo, et al.
Published: (2025)

Measuring Teaching with LLMs
by: Hardy, Michael
Published: (2025)

The Political Preferences of LLMs
by: Rozado, David
Published: (2024)

Concrete Problems in AI Safety, Revisited
by: Raji, Inioluwa Deborah, et al.
Published: (2023)

Evaluating Patient Safety Risks in Generative AI: Development and Validation of a FMECA Framework for Generated Clinical Content
by: Bednarczyk, Lydie, et al.
Published: (2026)

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

Moral Mazes in the Era of LLMs
by: Nguyen, Dang, et al.
Published: (2026)

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

Towards Robust Evaluation of Unlearning in LLMs via Data Transformations
by: Joshi, Abhinav, et al.
Published: (2024)

AI Safety Should Prioritize the Future of Work
by: Hazra, Sanchaita, et al.
Published: (2025)

CR4T: Rewrite-Based Guardrails for Adolescent LLM Safety
by: An, Heajun, et al.
Published: (2026)

Are LLMs (Really) Ideological? An IRT-based Analysis and Alignment Tool for Perceived Socio-Economic Bias in LLMs
by: Wachter, Jasmin, et al.
Published: (2025)

Safety Evaluation and Enhancement of DeepSeek Models in Chinese Contexts
by: Zhang, Wenjing, et al.
Published: (2025)

Interpretability Framework for LLMs in Undergraduate Calculus
by: Dakshit, Sagnik, et al.
Published: (2025)

TherapyGym: Evaluating and Aligning Clinical Fidelity and Safety in Therapy Chatbots
by: Huang, Fangrui, et al.
Published: (2026)

Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine
by: Yang, Yifan, et al.
Published: (2024)

On the Credibility of Evaluating LLMs using Survey Questions
by: Libovický, Jindřich
Published: (2026)