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CounterMoral: Editing Morals in Language Models

arXiv 2603.27338 ↗First posted 28 Mar 2026cs.AIcited by 0

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Abstract (arXiv)

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.

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References · 16

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  2. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
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  4. 2022Locating and Editing Factual Associations in GPTcited by 2,609
  5. 2022Mass-Editing Memory in a Transformercited by 976
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  7. 2020Aligning AI With Shared Human Valuescited by 706
  8. 2022Memory-Based Model Editing at Scalecited by 443
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  10. 2023Can We Edit Factual Knowledge by In-Context Learning?cited by 284
  11. 2020Editable Neural Networkscited by 154
  12. 2023Inspecting and Editing Knowledge Representations in Language Modelscited by 140
4 more
  1. 2020Rewriting a Deep Generative Modelcited by 105
  2. 2023Can Language Models be Instructed to Protect Personal Information?cited by 46
  3. 2023A Survey on Knowledge Editing of Neural Networkscited by 34
  4. 2021Ethics of AI: A Systematic Literature Review of Principles and Challengescited by 18

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