Publications

All papers have been subject to peer review unless indicated otherwise. *indicates equal contributions.

Click on a paper to view its short summary.

Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation

The 60th Annual Meeting of the Association for Computational Linguistics (ACL-22), 2022

Our paper introduces continual few-shot relation learning (CFRL), a challenging yet practical problem and proposes a novel method for this problem that outperforms existing approaches.

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Citation: Chengwei Qin and Shafiq Joty. Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation. In the 60th Annual Meeting of the Association for Computational Linguistics (ACL-22 Oral).
Paper Link: https://openreview.net/forum?id=tN-UlSrCBgM

LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5

The Tenth International Conference on Learning Representations (ICLR-22), 2022

We define a challenging yet practical problem as Lifelong Few-shot Language Learning and propose a unified framework for it based on prompt tuning of T5.

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Citation: Chengwei Qin and Shafiq Joty. LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5. In the Tenth International Conference on Learning Representations (ICLR-22).
Paper Link: https://openreview.net/forum?id=HCRVf71PMF

VMS: Traffic balancing based on virtual switches in datacenter networks

IEEE 25th International Conference on Network Protocols (ICNP-17), 2017

We propose Virtual Multi-channel Scatter (VMS), a new traffic balancing solution in datacenter networks.

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Citation: Zhaogeng Li, Jun Bi, Yiran Zhang, Abdul Basit Dogar and Chengwei Qin . VMS: Traffic balancing based on virtual switches in datacenter networks. In IEEE 25th International Conference on Network Protocols (ICNP-17).
Paper Link: https://ieeexplore.ieee.org/abstract/document/8117566