Search Results for author: Yafang Wang

Found 10 papers, 1 papers with code

R2D2: Recursive Transformer based on Differentiable Tree for Interpretable Hierarchical Language Modeling

1 code implementation ACL 2021 Xiang Hu, Haitao Mi, Zujie Wen, Yafang Wang, Yi Su, Jing Zheng, Gerard de Melo

Human language understanding operates at multiple levels of granularity (e. g., words, phrases, and sentences) with increasing levels of abstraction that can be hierarchically combined.

Language Modelling

Query Distillation: BERT-based Distillation for Ensemble Ranking

no code implementations COLING 2020 Wangshu Zhang, Junhong Liu, Zujie Wen, Yafang Wang, Gerard de Melo

We present a novel two-stage distillation method for ranking problems that allows a smaller student model to be trained while benefitting from the better performance of the teacher model, providing better control of the inference latency and computational burden.

Knowledge Distillation

DAN: Dual-View Representation Learning for Adapting Stance Classifiers to New Domains

no code implementations13 Mar 2020 Chang Xu, Cecile Paris, Surya Nepal, Ross Sparks, Chong Long, Yafang Wang

We address the issue of having a limited number of annotations for stance classification in a new domain, by adapting out-of-domain classifiers with domain adaptation.

Domain Adaptation Representation Learning +1

Long Short-Term Sample Distillation

no code implementations2 Mar 2020 Liang Jiang, Zujie Wen, Zhongping Liang, Yafang Wang, Gerard de Melo, Zhe Li, Liangzhuang Ma, Jiaxing Zhang, Xiaolong Li, Yuan Qi

The long-term teacher draws on snapshots from several epochs ago in order to provide steadfast guidance and to guarantee teacher--student differences, while the short-term one yields more up-to-date cues with the goal of enabling higher-quality updates.

Which Channel to Ask My Question? Personalized Customer Service RequestStream Routing using DeepReinforcement Learning

no code implementations24 Nov 2019 Zining Liu, Chong Long, Xiaolu Lu, Zehong Hu, Jie Zhang, Yafang Wang

These observations suggest that our proposed method can seek the trade-off where both channel resources and customers' satisfaction are optimal.

Chatbot Q-Learning +2

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