Papers by Jaspreet Singh
AMUSED: A Multi-Stream Vector Representation Method for Use in Natural Dialogue (2020.lrec-1)
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| Challenge: | Current architectures only take care of semantic and contextual information for a given query and fail to fully account for syntactic and external knowledge which are crucial for generating responses in a chit-chat system. |
| Approach: | They propose a multi-stream deep learning architecture that learns unified embeddings for query-response pairs by incorporating Graph Convolution Networks over their dependency parse. |
| Outcome: | The proposed architecture improves on the next sentence prediction task and significantly improves existing techniques. |
Asynchronous Convergence in Multi-Task Learning via Knowledge Distillation from Converged Tasks (2022.naacl-industry)
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Weiyi Lu, Sunny Rajagopalan, Priyanka Nigam, Jaspreet Singh, Xiaodi Sun, Yi Xu, Belinda Zeng, Trishul Chilimbi
| Challenge: | Multi-task learning (MTL) aims to solve multiple tasks by sharing a base representation among them. |
| Approach: | They propose an approach that allows for "asynchronous" convergence among the tasks where each task can converge on its own schedule. |
| Outcome: | The proposed method outperforms existing methods in two 5-task MTL setups. |