Papers by Hrishikesh Kulkarni
TBD3: A Thresholding-Based Dynamic Depression Detection from Social Media for Low-Resource Users (2022.lrec-1)
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| Challenge: | Social media are heavily used by many users to share their mental health concerns and diagnoses. |
| Approach: | They propose a dynamic thresholding technique that adjusts the classifier’s sensitivity as a function of the number of posts a user has. |
| Outcome: | The proposed method reduces the margin between users with many and few posts, on average, by 45% across all methods and increases overall performance, onaverage, by 33%. |
High-Quality Dialogue Diversification by Intermittent Short Extension Ensembles (2021.findings-acl)
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| Challenge: | Many task-oriented dialogue systems use deep reinforcement learning (DRL) to learn policies that respond to the user appropriately and complete the tasks successfully. |
| Approach: | They propose a method to diversify dialogues using a set of user models by constraining the intensity to interact with diverse user models. |
| Outcome: | The proposed method improves the performance of several state-of-the-art DRL dialogue agents trained in simulators. |