Papers by Ningning Ding

1 papers
CiPO: Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization (2026.acl-long)

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Challenge: Existing methods to unlearning large reasoning models do not remove unwanted knowledge from CoT traces or interfere with the reasoning process.
Approach: They propose a framework that targets the CoT reasoning in Large Reasoning Models by generating a valid counterfactual reasoning trace for preference tuning.
Outcome: Experiments on large LRMs show that CiPO completely removes knowledge from the intermediate CoT steps and the final answer while preserving the reasoning abilities of LRM.

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