Search Results for author: Zibo Lin

Found 5 papers, 2 papers with code

When Video Classification Meets Incremental Classes

no code implementations30 Jun 2021 Hanbin Zhao, Xin Qin, Shihao Su, Yongjian Fu, Zibo Lin, Xi Li

With the rapid development of social media, tremendous videos with new classes are generated daily, which raise an urgent demand for video classification methods that can continuously update new classes while maintaining the knowledge of old videos with limited storage and computing resources.

Classification class-incremental learning +3

Dialogue Response Selection with Hierarchical Curriculum Learning

1 code implementation ACL 2021 Yixuan Su, Deng Cai, Qingyu Zhou, Zibo Lin, Simon Baker, Yunbo Cao, Shuming Shi, Nigel Collier, Yan Wang

As for IC, it progressively strengthens the model's ability in identifying the mismatching information between the dialogue context and a response candidate.

Conversational Response Selection

Answer-driven Deep Question Generation based on Reinforcement Learning

no code implementations COLING 2020 Liuyin Wang, Zihan Xu, Zibo Lin, Haitao Zheng, Ying Shen

First, we propose an answer-aware initialization module with a gated connection layer which introduces both document and answer information to the decoder, thus helping to guide the choice of answer-focused question words.

Question Generation Question-Generation +2

The World is Not Binary: Learning to Rank with Grayscale Data for Dialogue Response Selection

no code implementations EMNLP 2020 Zibo Lin, Deng Cai, Yan Wang, Xiaojiang Liu, Hai-Tao Zheng, Shuming Shi

Despite that response selection is naturally a learning-to-rank problem, most prior works take a point-wise view and train binary classifiers for this task: each response candidate is labeled either relevant (one) or irrelevant (zero).

Conversational Response Selection Learning-To-Rank +2

Event Detection with Trigger-Aware Lattice Neural Network

1 code implementation IJCNLP 2019 Ning Ding, Ziran Li, Zhiyuan Liu, Hai-Tao Zheng, Zibo Lin

To ad- dress the two issues simultaneously, we pro- pose the Trigger-aware Lattice Neural Net- work (TLNN).

Event Detection

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