Search Results for author: Yijun Wang

Found 23 papers, 9 papers with code

Pre-training Entity Relation Encoder with Intra-span and Inter-span Information

no code implementations EMNLP 2020 Yijun Wang, Changzhi Sun, Yuanbin Wu, Junchi Yan, Peng Gao, Guotong Xie

In particular, a span encoder is trained to recover a random shuffling of tokens in a span, and a span pair encoder is trained to predict positive pairs that are from the same sentences and negative pairs that are from different sentences using contrastive loss.

Relation Relation Extraction +1

汉语学习者依存句法树库构建(Construction of a Treebank of Learner Chinese)

no code implementations CCL 2020 Jialu Shi, Xinyu Luo, Liner Yang, Dan Xiao, Zhengsheng Hu, Yijun Wang, Jiaxin Yuan, Yu Jingsi, Erhong Yang

汉语学习者依存句法树库为非母语者语料提供依存句法分析, 可以支持第二语言教学与研究, 也对面向第二语言的句法分析、语法改错等相关研究具有重要意义。然而, 现有的汉语学习者依存句法树库数量较少, 且在标注方面仍存在一些问题。为此, 本文改进依存句法标注规范, 搭建在线标注平台, 并开展汉语学习者依存句法标注。本文重点介绍了数据选取、标注流程等问题, 并对标注结果进行质量分析, 探索二语偏误对标注质量与句法分析的影响。

Learning to Denoise Unreliable Interactions for Link Prediction on Biomedical Knowledge Graph

no code implementations9 Dec 2023 Tengfei Ma, Yujie Chen, Wen Tao, Dashun Zheng, Xuan Lin, Patrick Cheong-lao Pang, Yiping Liu, Yijun Wang, Bosheng Song, Xiangxiang Zeng

By maximizing the mutual information between the reliable structure and smoothed semantic relations, DenoisedLP emphasizes the informative interactions for predicting relation-specific links.

Denoising Drug Discovery +2

Visual tracking brain computer interface

no code implementations21 Nov 2023 Changxing Huang, Nanlin Shi, Yining Miao, Xiaogang Chen, Yijun Wang, Xiaorong Gao

Brain-computer interfaces (BCIs) offer a way to interact with computers without relying on physical movements.

Brain Computer Interface Continuous Control +2

Breathing Life into Faces: Speech-driven 3D Facial Animation with Natural Head Pose and Detailed Shape

no code implementations31 Oct 2023 Wei Zhao, Yijun Wang, Tianyu He, Lianying Yin, Jianxin Lin, Xin Jin

To augment the richness of 3D facial animation, we construct a new 3D dataset with detailed shapes and learn to synthesize facial details in line with speech content.

Decoding Natural Images from EEG for Object Recognition

2 code implementations25 Aug 2023 Yonghao Song, Bingchuan Liu, Xiang Li, Nanlin Shi, Yijun Wang, Xiaorong Gao

This paper presents a self-supervised framework to demonstrate the feasibility of learning image representations from EEG signals, particularly for object recognition.

Contrastive Learning EEG +2

DiffColor: Toward High Fidelity Text-Guided Image Colorization with Diffusion Models

no code implementations3 Aug 2023 Jianxin Lin, Peng Xiao, Yijun Wang, Rongju Zhang, Xiangxiang Zeng

To address these issues, we propose a new method called DiffColor that leverages the power of pre-trained diffusion models to recover vivid colors conditioned on a prompt text, without any additional inputs.

Colorization Image Colorization +1

EMoG: Synthesizing Emotive Co-speech 3D Gesture with Diffusion Model

no code implementations20 Jun 2023 Lianying Yin, Yijun Wang, Tianyu He, Jinming Liu, Wei Zhao, Bohan Li, Xin Jin, Jianxin Lin

In this paper, we present a novel framework (EMoG) to tackle the above challenges with denoising diffusion models: 1) To alleviate the one-to-many problem, we incorporate emotion clues to guide the generation process, making the generation much easier; 2) To model joint correlation, we propose to decompose the difficult gesture generation into two sub-problems: joint correlation modeling and temporal dynamics modeling.

Denoising Gesture Generation

NRTR: Neuron Reconstruction with Transformer from 3D Optical Microscopy Images

no code implementations8 Dec 2022 Yijun Wang, Rui Lang, Rui Li, Junsong Zhang

Existing deep learning neuron reconstruction methods, although demonstrating exemplary performance, greatly demand complex rule-based components.

Few Clean Instances Help Denoising Distant Supervision

1 code implementation COLING 2022 Yufang Liu, Ziyin Huang, Yijun Wang, Changzhi Sun, Man Lan, Yuanbin Wu, Xiaofeng Mou, Ding Wang

Existing distantly supervised relation extractors usually rely on noisy data for both model training and evaluation, which may lead to garbage-in-garbage-out systems.


Asynchronous Hierarchical Federated Learning

no code implementations31 May 2022 Xing Wang, Yijun Wang

Federated Learning is a rapidly growing area of research and with various benefits and industry applications.

Federated Learning Image Classification

YACLC: A Chinese Learner Corpus with Multidimensional Annotation

1 code implementation30 Dec 2021 Yingying Wang, Cunliang Kong, Liner Yang, Yijun Wang, Xiaorong Lu, Renfen Hu, Shan He, Zhenghao Liu, Yun Chen, Erhong Yang, Maosong Sun

This resource is of great relevance for second language acquisition research, foreign-language teaching, and automatic grammatical error correction.

Grammatical Error Correction Language Acquisition +1

ENPAR:Enhancing Entity and Entity Pair Representations for Joint Entity Relation Extraction

1 code implementation EACL 2021 Yijun Wang, Changzhi Sun, Yuanbin Wu, Hao Zhou, Lei LI, Junchi Yan

Current state-of-the-art systems for joint entity relation extraction (Luan et al., 2019; Wad-den et al., 2019) usually adopt the multi-task learning framework.

coreference-resolution Entity Typing +5

Gravitational Wave Detection with Photometric Surveys

1 code implementation5 Oct 2020 Yijun Wang, Kris Pardo, Tzu-Ching Chang, Olivier Doré

While the detection threshold assuming the currently expected performance proves too high for detecting individual GWs in light of the expected supermassive black hole binary population distribution, we show that binaries with chirp mass $M_c>10^{8. 3}~M_\odot$ out to 100 Mpc can be detected if the telescope is able to achieve an astrometric accuracy of 0. 11 mas.

General Relativity and Quantum Cosmology Cosmology and Nongalactic Astrophysics

MMEA: Entity Alignment for Multi-Modal Knowledge Graphs

1 code implementation20 Aug 2020 Liyi Chen, Zhi Li, Yijun Wang, Tong Xu, Zhefeng Wang, Enhong Chen

To that end, in this paper, we propose a novel solution called Multi-Modal Entity Alignment (MMEA) to address the problem of entity alignment in a multi-modal view.

Knowledge Graphs Multimodal Deep Learning +1

Learning to Transfer: Unsupervised Meta Domain Translation

1 code implementation1 Jun 2019 Jianxin Lin, Yijun Wang, Tianyu He, Zhibo Chen

Unsupervised domain translation has recently achieved impressive performance with Generative Adversarial Network (GAN) and sufficient (unpaired) training data.

Generative Adversarial Network Meta-Learning +1

Image-to-Image Translation with Multi-Path Consistency Regularization

no code implementations29 May 2019 Jianxin Lin, Yingce Xia, Yijun Wang, Tao Qin, Zhibo Chen

In this work, we introduce a new kind of loss, multi-path consistency loss, which evaluates the differences between direct translation $\mathcal{D}_s\to\mathcal{D}_t$ and indirect translation $\mathcal{D}_s\to\mathcal{D}_a\to\mathcal{D}_t$ with $\mathcal{D}_a$ as an auxiliary domain, to regularize training.

Face to Face Translation Image-to-Image Translation +1

Ensemble Pruning based on Objection Maximization with a General Distributed Framework

1 code implementation13 Jun 2018 Yijun Bian, Yijun Wang, Yaqiang Yao, Huanhuan Chen

Ensemble pruning, selecting a subset of individual learners from an original ensemble, alleviates the deficiencies of ensemble learning on the cost of time and space.

Ensemble Learning Ensemble Pruning

Classifying Single-Trial EEG during Motor Imagery with a Small Training Set

no code implementations14 Jun 2013 Yijun Wang

Before the operation of a motor imagery based brain-computer interface (BCI) adopting machine learning techniques, a cumbersome training procedure is unavoidable.

BIG-bench Machine Learning EEG +1

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