Probing Narrative Morals: A New Character-Focused MFT Framework for Use with Large Language Models (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods to categorize moral foundations in storytelling are limited. |
| Approach: | They propose a character-centric method to quantify moral foundations in storytelling using large language models and a novel Moral Foundations Character Action Questionnaire to validate their approach against human annotations. |
| Outcome: | The proposed method validates against human annotations and then applies to 2,697 folktales from 55 countries. |
Similar Papers
Moral Foundations of Large Language Models (2024.emnlp-main)
Copied to clipboard
| Challenge: | Moral foundations theory (MFT) is a psychological assessment tool that decomposes human moral reasoning into five factors, including care/harm, liberty/oppression, and sanctity/degradation. |
| Approach: | They propose to use moral foundations theory to analyze whether popular LLMs have acquired a bias towards a particular set of moral values. |
| Outcome: | The proposed model can be adversarially selected to exhibit a particular moral foundations and can affect downstream tasks. |
Story Morals: Surfacing value-driven narrative schemas using large language models (2024.emnlp-main)
Copied to clipboard
| Challenge: | Using large language models, we extract and validate story morals across a diverse set of narrative genres. |
| Approach: | They propose a task of narrative schema labelling based on the concept of "story morals" they use large language models to extract and validate story morals across a diverse set of genres . |
| Outcome: | The proposed method extracts and validates story morals across folktales, novels, movies and TV, personal stories from social media and the news using automated metrics and human assessments. |
Tales of Morality: Comparing Human- and LLM-Generated Moral Stories from Visual Cues (2025.findings-emnlp)
Copied to clipboard
| Challenge: | a recent study has found that stories are central to how humans communicate moral values . |
| Approach: | They compare human- and LLM-generated moral narratives based on images annotated by humans for moral content . authors propose a framework for evaluating moral storytelling in vision-language models . |
| Outcome: | The proposed model compared human- and LLM-generated narratives on images . human stories reflect a balanced distribution of moral foundations and coherent narrative arcs, but LLMs emphasize Care foundation and lack emotional resolution. |
MFTCXplain: A Multilingual Benchmark Dataset for Evaluating the Moral Reasoning of LLMs through Multi-hop Hate Speech Explanation (2025.findings-emnlp)
Copied to clipboard
Jackson Trager, Francielle Vargas, Diego Alves, Matteo Guida, Mikel K. Ngueajio, Ameeta Agrawal, Yalda Daryani, Farzan Karimi Malekabadi, Flor Miriam Plaza-del-Arco
| Challenge: | Existing evaluation benchmarks for large language models lack annotations that justify moral classifications and focus on English constrain moral reasoning across diverse cultural settings. |
| Approach: | They propose a multilingual benchmark dataset for evaluating moral reasoning of large language models . it includes 3,000 tweets annotated with binary hate speech labels, moral categories and rationales . |
| Outcome: | The proposed dataset shows a misalignment between LLM outputs and human annotations in moral reasoning tasks. |
Moral Framing in Politics (MFiP): A new resource and models for moral framing (2025.emnlp-main)
Copied to clipboard
| Challenge: | Recent studies have focused on detecting moral values in political communication, trying to identify moral frames used by political actors or parties to convey their messages. |
| Approach: | They propose to code German parliamentary debates to identify moral framing and to detect subtle differences in politicians’ moral framming. |
| Outcome: | The proposed model distinguishes between different types of moral frames and includes narrative roles, together with the moral foundations for each frame. |
Exploring LLMs’ Ability to Spontaneously and Conditionally Modify Moral Expressions through Text Manipulation (2025.acl-long)
Copied to clipboard
| Challenge: | Existing studies on moral-related tasks based on large language models have not been conducted. |
| Approach: | They analyze behavior of Large Language Models (LLMs) among open and uncensored models and use human-annotated datasets to analyze moral-related data. |
| Outcome: | The results show that large language models can alter moral dimensions through text manipulation tasks and moral-related conditioning prompts. |
Are Rules Meant to be Broken? Understanding Multilingual Moral Reasoning as a Computational Pipeline with UniMoral (2025.acl-long)
Copied to clipboard
| Challenge: | Existing approaches to analyze moral reasoning are discordant and lack cohesion, focusing on isolated aspects of the process. |
| Approach: | They propose a unified dataset that integrates moral dilemmas annotated with labels for action choices, ethical principles, contributing factors, and consequences, and captures diverse socio-cultural contexts. |
| Outcome: | The proposed dataset integrates moral dilemmas annotated with labels for action choices, ethical principles, contributing factors, and consequences, along with annotators’ moral and cultural profiles. |
Adaptable Moral Stances of Large Language Models on Sexist Content: Implications for Society and Gender Discourse (2024.emnlp-main)
Copied to clipboard
| Challenge: | Using large language models, large language model learning has become more integrated into our daily lives, making it increasingly important to ensure they reflect ethical and equitable values. |
| Approach: | They assess how LLMs can apply moral reasoning to both criticize and defend sexist language by evaluating their models and evaluating the moral foundations cited by them. |
| Outcome: | The models show they can provide comprehensible and contextually relevant text for understanding diverse views on how sexism is perceived. |
Evaluating Moral Beliefs across LLMs through a Pluralistic Framework (2024.findings-emnlp)
Copied to clipboard
| Challenge: | Proper moral beliefs are fundamental for language models, yet assessing these beliefs poses a significant challenge. |
| Approach: | They propose a framework to evaluate the moral beliefs of four large language models . they use a dataset containing 472 moral choice scenarios in Chinese . |
| Outcome: | The proposed framework evaluates the moral beliefs of four large language models. |
CharMoral: A Character Morality Dataset for Morally Dynamic Character Analysis in Long-Form Narratives (2025.coling-main)
Copied to clipboard
| Challenge: | Existing studies on character analysis focus on character identification, social network analysis, and the exploration of characters' personas or personalities. |
| Approach: | They propose a four-stage framework to automatically classify actions as moral or immoral based on context. |
| Outcome: | The proposed framework is effective in moral reasoning tasks in multiple genres. |