CounterMoral: Editing Morals in Language Models

Computer Science > Artificial Intelligence [Submitted on 28 Mar 2026] CounterMoral: Editing Morals in Language Models Michael Ripa, Jim Davies Recent advancements in language model technology have significantly enhanced the ability to edit factual information. Yet, the modification of moral judgments, a crucial aspect of aligning models with human values, has garnered less attention. In this work, we introduce CounterMoral, a benchmark dataset crafted to assess how well current model editing techniques modify moral judgments across diverse ethical frameworks. We apply various editing techniques to multiple language models and evaluate their performance. Our findings contribute to the evaluation of language models designed to be ethical. Comments: 7 pages (10 + 1 reference + 6 appendix). Honors thesis completed in June 2024, write-up completed in 2025 Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2603.27338 [cs.AI]   (or arXiv:2603.27338v1 [cs.AI] for this version)   https://doi.org/10.48550/arXiv.2603.27338 Focus to learn more Submission history From: Michael Ripa [view email] [v1] Sat, 28 Mar 2026 17:13:30 UTC (192 KB) Access Paper: HTML (experimental) view license Current browse context: cs.AI < prev   |   next > new | recent | 2026-03 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar Export BibTeX Citation Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Demos Related Papers About arXivLabs Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)