most citedInterpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making

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cs.CL2021★ 1 cited

Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making

Zijun Yao, Chengjiang Li, Tiansi Dong +6

Entity Matching (EM) aims at recognizing entity records that denote the same real-world object. Neural EM models learn vector representation of entity descriptions and match entiti…

cs.CL2019

Multiple Generative Models Ensemble for Knowledge-Driven Proactive Human-Computer Dialogue Agent

Zelin Dai, Weitang Liu, Guanhua Zhan

Multiple sequence to sequence models were used to establish an end-to-end multi-turns proactive dialogue generation agent, with the aid of data augmentation techniques and variant…