arXiv AI August 14, 2026 By Erica Coppolillo, Emilio Ferrara

MOSAIC: Unveiling the Moral, Social and Individual Dimensions of Large Language Models

arXiv:2603. 00048v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed in sensitive applications including psychological support, healthcare, and high-stakes decision-making.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv AI

Jun 12

MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

arXiv:2510. 16380v2 Announce Type: replace-cross Abstract: As AI systems progress, we rely more on them to make decisions with us and for us.

By Yu Ying Chiu, Michael S. Lee, Rachel Calcott, Brandon Handoko, Paul de Font-Reaulx, Rapha\"el Milli\`ere, Paula Rodriguez, Chen Bo Calvin Zhang, Ziwen Han, Udari Madhushani Sehwag, Yash Maurya, Christina Q Knight, Harry R. Lloyd, Florence Bacus, Conor Downey, Mantas Mazeika, Bing Liu, Yejin Choi, Mitchell L Gordon, Sydney Levine

llms benchmarks

arXiv AI

Jun 11

Are LLMs Bad at Moral Reasoning?

arXiv:2606. 11635v1 Announce Type: cross Abstract: For highly capable AI systems to operate safely in dynamic, open-ended environments, they must be able to identify, understand, and respond to moral reasons for action, and constrain their behaviour accordingly.

By Menghang Zhu, Seth Lazar

llms benchmarks

arXiv AI

1d ago

Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture

arXiv:2608. 14566v1 Announce Type: new Abstract: Recent work on evaluating the moral competence of large language models (LLMs) has focused primarily on what we call the moral value problem, i.

By Aidan Kierans, Ritam Dutt, Kaley Rittichier, Shiri Dori-Hacohen, Avijit Ghosh

llms benchmarks

arXiv AI

Jun 12

LLMs Can Better Capture Human Judgments--With the Right Prompts

arXiv:2606. 12754v1 Announce Type: cross Abstract: Are large language models (LLMs) bad at capturing human judgment?

By Danica Dillion, Chen Cecilia Liu, Baihui Wang, Daniele Barolo, Tanmay Rajore, Niket Tandon, Pranathi Ravikumar, Kurt Gray

llms safety

arXiv AI

5d ago

Agreement Is Not Alignment: Divergent Moral Grounds in Human and LLM Ethical Judgments

arXiv:2608. 12368v1 Announce Type: new Abstract: Agreement with human judgments is a common proxy for evaluating the alignment of large language models (LLMs).

By Octavian M. Machidon, Alina L. Machidon, Vojko Strahovnik, Mateja Centa Strahovnik, Jonas Miklav\v{c}i\v{c}, Marko Robnik \v{S}ikonja

llms agents benchmarks safety

arXiv AI

Jul 14

Toward Contemplative LLM: A Modular Framework for Evaluating and Enhancing LLM Alignment in Mental Health

arXiv:2607. 10871v1 Announce Type: new Abstract: Contemplative traditions have long guided ethical behavior and prosocial interaction, and recent work suggests that contemplative principles (e.

By Asher Sprigler, Yang-Yang Feng, Iftach Amir, Jonathan E. Bogard, Todd S Braver, Yi Ding, David Kinney, Yixue Zhao

llms benchmarks safety

Related stories

MoReBench: Evaluating Procedural and Pluralistic Moral Reasoning in Language Models, More than Outcomes

Are LLMs Bad at Moral Reasoning?

Position: Evaluations of AI Moral Reasoning Still Miss Half of the Picture

LLMs Can Better Capture Human Judgments--With the Right Prompts

Agreement Is Not Alignment: Divergent Moral Grounds in Human and LLM Ethical Judgments

Toward Contemplative LLM: A Modular Framework for Evaluating and Enhancing LLM Alignment in Mental Health