Papers by Clint Solomon Mathialagan
Self-Aware Feedback-Based Self-Learning in Large-Scale Conversational AI (2022.naacl-industry)
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| Challenge: | Large-scale conversational AI systems require constant update to adapt to changing customer behavior and trends . lack of self-awareness in feedback-based systems can cause degradation of performance . et al., e. alderman and scott k. d. argues that such systems are not scalable enough to sustain the rapid update pace of conversational systems. |
| Approach: | They propose a superposition-based model that reactively learns local-adaptive decision boundaries . they propose rewritings with a bi-variate beta setting to improve the model's performance . |
| Outcome: | The proposed model improves the PR-AUC by 27.45% and reduces relative defect reductions by 31.22% . the proposed model can adapt faster to changes in global preferences across a large number of customers . |