Papers by Arindam Bhattacharya
CUPID: Curriculum Learning Based Real-Time Prediction using Distillation (2023.acl-industry)
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| Challenge: | Relevance in E-commerce Product Search is crucial for providing customers with accurate results that match their query intent. |
| Approach: | They propose a curriculum learning based real-time relevance prediction using distillation . they propose e-commerce search systems that use transformers to predict relevance . |
| Outcome: | The proposed model improves on english and Arabic in a bi-lingual relevance prediction task while maintaining low evaluation latency on CPUs. |
Generative or Discriminative? Revisiting Text Classification in the Era of Transformers (2025.emnlp-main)
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Siva Rajesh Kasa, Karan Gupta, Sumegh Roychowdhury, Ashutosh Kumar, Yaswanth Biruduraju, Santhosh Kumar Kasa, Pattisapu Nikhil Priyatam, Arindam Bhattacharya, Shailendra Agarwal, Vijay Huddar
| Challenge: | generative classifiers exhibit lower sample complexity but higher asymptotic error in simple linear settings, a trade-off that remains unexplored in the transformer era. |
| Approach: | They propose to evaluate generative and discriminative architectures for text classification using a generative model that learns the conditional probability distribution P (y|x) generative models are known to work better in low-data settings, giving rise to the classical 'two regimes' phenomenon for classification. |
| Outcome: | The proposed models show that the classical 'two regimes' manifests distinctly across different architectures and training paradigms. |