mlsanityData to 7 Oct 2026

A Data Fusion Framework for Multi-Domain Morality Learning

arXiv 2304.02144 ↗First posted 4 Apr 2023cs.CLcited by 14

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Abstract (arXiv)

Language models can be trained to recognize the moral sentiment of text, creating new opportunities to study the role of morality in human life. As interest in language and morality has grown, several ground truth datasets with moral annotations have been released. However, these datasets vary in the method of data collection, domain, topics, instructions for annotators, etc. Simply aggregating such heterogeneous datasets during training can yield models that fail to generalize well. We describe a data fusion framework for training on multiple heterogeneous datasets that improve performance and generalizability. The model uses domain adversarial training to align the datasets in feature space and a weighted loss function to deal with label shift. We show that the proposed framework achieves state-of-the-art performance in different datasets compared to prior works in morality inference.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Builds on 21 of its 47 references that are in the map. First posted on arXiv 4 Apr 2023.

Builds on

21 of 47 references.

References · 21

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
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  5. 2020Social Chemistry 101: Learning to Reason about Social and Moral Normscited by 253
  6. 2021Large Pre-trained Language Models Contain Human-like Biases of What is Right and Wrong to Docited by 178
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  12. 2020Moral Framing and Ideological Bias of Newscited by 29
9 more
  1. 2017Acquiring Background Knowledge to Improve Moral Value Predictioncited by 22
  2. 2022The Moral Foundations Reddit Corpuscited by 20
  3. 2022A Holistic Framework for Analyzing the COVID-19 Vaccine Debatecited by 18
  4. 2022Learning Semantic Segmentation from Multiple Datasets with Label Shiftscited by 14
  5. 2021Crowdsourcing Learning as Domain Adaptation: A Case Study on Named Entity Recognitioncited by 13
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  7. 2021Modeling Ideological Salience and Framing in Polarized Online Groups with Graph Neural Networks and Structured Sparsitycited by 9
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Citing papers per year: 2023: 1; 2024: 7; 2025: 3; 2026: 3.

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  1. 2024Emergence of Social Norms in Generative Agent Societies: Principles and Architecturecited by 41
  2. 2024MoralBERT: A Fine-Tuned Language Model for Capturing Moral Values in Social Discussionscited by 23
  3. 2024Whose Emotions and Moral Sentiments Do Language Models Reflect?cited by 20
  4. 2025MoVa: Towards Generalizable Classification of Human Morals and Valuescited by 7
  5. 2023Inducing Political Bias Allows Language Models Anticipate Partisan Reactions to Controversiescited by 4
  6. 2024Estimating Causal Effects of Text Interventions Leveraging LLMscited by 4
  7. 2024A Survey on Moral Foundation Theory and Pre-Trained Language Models: Current Advances and Challengescited by 3
  8. 2025Fairness Metric Design Exploration in Multi-Domain Moral Sentiment Classification using Transformer-Based Modelscited by 2
  9. 2024#EpiTwitter: Public Health Messaging During the COVID-19 Pandemiccited by 0
  10. 2024Do Language Models Understand Morality? Towards a Robust Detection of Moral Contentcited by 0
  11. 2025MoralCLIP: Contrastive Alignment of Vision-and-Language Representations with Moral Foundations Theorycited by 0
  12. 2026TWeddit : A Dataset of Triggering Stories Predominantly Shared by Women on Redditcited by 0
2 more
  1. 2026Learning Moral Diversity: Modelling Individual Perspectives in Moral Classification of Textscited by 0
  2. 2026Less Is Moral: A CHARMing Framework for Moral Foundations Detection in Endorsement Behaviourcited by 0