Papers with likelihood-based classification

1 papers
Sampling-based Pseudo-Likelihood for Membership Inference Attacks (2025.findings-acl)

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Challenge: Large Language Models (LLMs) are trained on large-scale web data, which makes it difficult to grasp the contribution of each text.
Approach: They propose a membership-inference attack method that uses only the input text to detect leaks.
Outcome: The proposed method performs on par with existing likelihood-based methods even without likelihoods.

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