Search Results for author: Wenbin Jiang

Found 26 papers, 2 papers with code

A Transition-based Method for Complex Question Understanding

no code implementations COLING 2022 Yu Xia, Wenbin Jiang, Yajuan Lyu, Sujian Li

Existing works are based on end-to-end neural models which do not explicitly model the intermediate states and lack interpretability for the parsing process.

Dynamic Multistep Reasoning based on Video Scene Graph for Video Question Answering

no code implementations NAACL 2022 Jianguo Mao, Wenbin Jiang, Xiangdong Wang, Zhifan Feng, Yajuan Lyu, Hong Liu, Yong Zhu

Then, it performs multistep reasoning for better answer decision between the representations of the question and the video, and dynamically integrate the reasoning results.

Question Answering Video Question Answering +1

Improving Video Retrieval by Adaptive Margin

no code implementations9 Mar 2023 Feng He, Qi Wang, Zhifan Feng, Wenbin Jiang, Yajuan Lv, Yong Zhu, Xiao Tan

While most video retrieval methods overlook that phenomenon, we propose an adaptive margin changed with the distance between positive and negative pairs to solve the aforementioned issue.

Retrieval Video Retrieval

Neural Knowledge Bank for Pretrained Transformers

no code implementations31 Jul 2022 Damai Dai, Wenbin Jiang, Qingxiu Dong, Yajuan Lyu, Qiaoqiao She, Zhifang Sui

The ability of pretrained Transformers to remember factual knowledge is essential but still limited for existing models.

Language Modelling Machine Translation +2

Mixture of Experts for Biomedical Question Answering

no code implementations15 Apr 2022 Damai Dai, Wenbin Jiang, Jiyuan Zhang, Weihua Peng, Yajuan Lyu, Zhifang Sui, Baobao Chang, Yong Zhu

In this paper, in order to alleviate the parameter competition problem, we propose a Mixture-of-Expert (MoE) based question answering method called MoEBQA that decouples the computation for different types of questions by sparse routing.

Question Answering

Masks Fusion with Multi-Target Learning For Speech Enhancement

1 code implementation23 Sep 2021 Liangchen Zhou, Wenbin Jiang, Jingyan Xu, Fei Wen, Peilin Liu

Typically, a single T-F mask is first estimated based on DNN and then used to mask the spectrogram of noisy speech in an order to suppress the noise.

Speech Enhancement

Multi-view Classification Model for Knowledge Graph Completion

no code implementations Asian Chapter of the Association for Computational Linguistics 2020 Wenbin Jiang, Mengfei Guo, Yufeng Chen, Ying Li, Jinan Xu, Yajuan Lyu, Yong Zhu

This paper describes a novel multi-view classification model for knowledge graph completion, where multiple classification views are performed based on both content and context information for candidate triple evaluation.

Classification Knowledge Graph Completion

CoKE: Contextualized Knowledge Graph Embedding

3 code implementations6 Nov 2019 Quan Wang, Pingping Huang, Haifeng Wang, Songtai Dai, Wenbin Jiang, Jing Liu, Yajuan Lyu, Yong Zhu, Hua Wu

This work presents Contextualized Knowledge Graph Embedding (CoKE), a novel paradigm that takes into account such contextual nature, and learns dynamic, flexible, and fully contextualized entity and relation embeddings.

Knowledge Graph Embedding Link Prediction +1

An Automatic Machine Translation Evaluation Metric Based on Dependency Parsing Model

no code implementations9 Aug 2015 Hui Yu, Xiaofeng Wu, Wenbin Jiang, Qun Liu, ShouXun Lin

To avoid these problems, we propose a novel automatic evaluation metric based on dependency parsing model, with no need to define sub-structures by human.

Dependency Parsing Machine Translation +2

$gen$CNN: A Convolutional Architecture for Word Sequence Prediction

no code implementations17 Mar 2015 Mingxuan Wang, Zhengdong Lu, Hang Li, Wenbin Jiang, Qun Liu

Different from previous work on neural network-based language modeling and generation (e. g., RNN or LSTM), we choose not to greedily summarize the history of words as a fixed length vector.

Language Modelling Machine Translation +3

Encoding Source Language with Convolutional Neural Network for Machine Translation

no code implementations IJCNLP 2015 Fandong Meng, Zhengdong Lu, Mingxuan Wang, Hang Li, Wenbin Jiang, Qun Liu

The recently proposed neural network joint model (NNJM) (Devlin et al., 2014) augments the n-gram target language model with a heuristically chosen source context window, achieving state-of-the-art performance in SMT.

Language Modelling Machine Translation +2

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