Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Do Moral Judgment and Reasoning Capability of LLMs Change with Language? A Study using the Multilingual Defining Issues Test

Domain:

natural language processing

Record type:

paper
Creator:
KhaAgaTanCho
Host:avatar
This paper explores the moral judgment and moral reasoning abilities exhibited by Large Language Models (LLMs) across languages through the Defining Issues Test. It is a well known fact that moral judgment depends on the language in which the question is asked. We extend the work of beyond English, to 5 new languages (Chinese, Hindi, Russian, Spanish and Swahili), and probe three LLMs -- ChatGPT, GPT-4 and Llama2Chat-70B -- that shows substantial multilingual text processing and generation abilities. Our study shows that the moral reasoning ability for all models, as indicated by the post-conventional score, is substantially inferior for Hindi and Swahili, compared to Spanish, Russian, Chinese and English, while there is no clear trend for the performance of the latter four languages. The moral judgments too vary considerably by the language. Accepted to EACL 2024 (main)

Visit

arxiv.org

Languages

Swahili

Tags

Computation and LanguageArtificial Intelligence

Similar

EMCEE: Improving Multilingual Capability of LLMs via Bridging Knowledge and Reasoning with Extracted Synthetic Multilingual ContextUnlocking Multilingual Reasoning Capability of LLMs and LVLMs through Representation EngineeringLLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual FeedbackEthical Reasoning and Moral Value Alignment of LLMs Depend on the Language we Prompt them inThe effect of foreign language and psychological distance on moral judgment in Turkish–English bilingualsOptimal Transport Distillation for Zero-Shot Cross-Lingual Reasoning in Multilingual LLMs

EMCEE: Improving Multilingual Capability of LLMs via Bridging Knowledge and Reasoning with Extracted Synthetic Multilingual Context

Large Language Models (LLMs) have achieved impressive progress across a wide range of tasks, yet the

Unlocking Multilingual Reasoning Capability of LLMs and LVLMs through Representation Engineering

Large Language Models (LLMs) and Large Vision-Language Models (LVLMs) demonstrate strong reasoning c

LLMs Beyond English: Scaling the Multilingual Capability of LLMs with Cross-Lingual Feedback

To democratize large language models (LLMs) to most natural languages, it is imperative to make thes

Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language we Prompt them in

Ethical reasoning is a crucial skill for Large Language Models (LLMs). However, moral values are not

The effect of foreign language and psychological distance on moral judgment in Turkish–English bilinguals

International audience

Optimal Transport Distillation for Zero-Shot Cross-Lingual Reasoning in Multilingual LLMs

Benefiting from transformer-based pre-trained language models, neural ranking models have made signi