Papers by Vaishnavi Shrivastava
UserIdentifier: Implicit User Representations for Simple and Effective Personalized Sentiment Analysis (2022.naacl-main)
Copied to clipboard
Fatemehsadat Mireshghallah, Vaishnavi Shrivastava, Milad Shokouhi, Taylor Berg-Kirkpatrick, Robert Sim, Dimitrios Dimitriadis
| Challenge: | Currently, global models are not able to produce personalized responses for individual users, based on their data. |
| Approach: | They propose a scheme for training a single shared model for all users by prepending a fixed, user-specific non-trainable string to each user’s input text. |
| Outcome: | The proposed method outperforms the state-of-the-art model on a suite of sentiment analysis datasets by up to 13 points. |