Papers by Janardhan Kulkarni
Assessing Privacy Risks in Language Models: A Case Study on Summarization Tasks (2023.findings-emnlp)
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| Challenge: | Large language models have revolutionized the field of NLP by achieving state-of-the-art performance on various tasks. |
| Approach: | They investigate the membership inference attack by using model's API to determine if a sample was part of the training data. |
| Outcome: | The proposed model is able to identify if a sample was part of the training data and exploits its similarity and resistance to document modifications as potential MI signals on widely used datasets. |