Papers by Marvin Li
CheckMIABench: Firm Foundations For Membership Inference Attacks on Language Models (2026.acl-short)
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| Challenge: | Membership inference attacks are a canonical way to assess a machine learning model’s privacy properties. |
| Approach: | They propose a framework for principled evaluation of membership inference attacks against large language models by leveraging the insight that training data before and after a fixed point during training are drawn from the same distribution. |
| Outcome: | The proposed framework can be used to evaluate membership inference attacks against large language models. |
MoPe: Model Perturbation based Privacy Attacks on Language Models (2023.emnlp-main)
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| Challenge: | Recent work shows that Large Language Models can unintentionally leak sensitive information . a new method to identify with high confidence if a given text is in training data is proposed . |
| Approach: | They propose a method to detect if a given text is in a pre-trained language model . they show that MoPe is more effective than existing loss-based attacks . |
| Outcome: | The proposed method is more effective than loss-based attacks and perturbation-based methods. |