Search Results for author: Chengyu Wang

Found 38 papers, 18 papers with code

UnClE: Explicitly Leveraging Semantic Similarity to Reduce the Parameters of Word Embeddings

no code implementations Findings (EMNLP) 2021 Zhi Li, Yuchen Zhai, Chengyu Wang, Minghui Qiu, Kailiang Li, Yin Zhang

Inspired by the fact that words with similar semantic can share a part of weights, we divide the embeddings of words into two parts: unique embedding and class embedding.

Language Modelling Semantic Similarity +2

Meta Distant Transfer Learning for Pre-trained Language Models

no code implementations EMNLP 2021 Chengyu Wang, Haojie Pan, Minghui Qiu, Jun Huang, Fei Yang, Yin Zhang

For tasks related to distant domains with different class label sets, PLMs may memorize non-transferable knowledge for the target domain and suffer from negative transfer.

Implicit Relations Meta-Learning +2

Refiner: Data Refining against Gradient Leakage Attacks in Federated Learning

no code implementations5 Dec 2022 Mingyuan Fan, Cen Chen, Chengyu Wang, Wenmeng Zhou, Jun Huang, Ximeng Liu, Wenzhong Guo

To craft robust data, Refiner promotes the gradients of critical parameters associated with robust data to close ground-truth ones while leaving the gradients of trivial parameters to safeguard privacy.

Federated Learning

TW-BAG: Tensor-wise Brain-aware Gate Network for Inpainting Disrupted Diffusion Tensor Imaging

no code implementations31 Oct 2022 Zihao Tang, Xinyi Wang, Lihaowen Zhu, Mariano Cabezas, Dongnan Liu, Michael Barnett, Weidong Cai, Chengyu Wang

Diffusion Weighted Imaging (DWI) is an advanced imaging technique commonly used in neuroscience and neurological clinical research through a Diffusion Tensor Imaging (DTI) model.

Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training

1 code implementation11 Oct 2022 Taolin Zhang, Junwei DOng, Jianing Wang, Chengyu Wang, Ang Wang, Yinghui Liu, Jun Huang, Yong Li, Xiaofeng He

Recently, knowledge-enhanced pre-trained language models (KEPLMs) improve context-aware representations via learning from structured relations in knowledge graphs, and/or linguistic knowledge from syntactic or dependency analysis.

Knowledge Graphs Language Modelling +2

Understanding Long Programming Languages with Structure-Aware Sparse Attention

1 code implementation27 May 2022 Tingting Liu, Chengyu Wang, Cen Chen, Ming Gao, Aoying Zhou

With top-$k$ sparse attention, the most crucial attention relation can be obtained with a lower computational cost.

Towards Unified Prompt Tuning for Few-shot Text Classification

1 code implementation11 May 2022 Jianing Wang, Chengyu Wang, Fuli Luo, Chuanqi Tan, Minghui Qiu, Fei Yang, Qiuhui Shi, Songfang Huang, Ming Gao

Prompt-based fine-tuning has boosted the performance of Pre-trained Language Models (PLMs) on few-shot text classification by employing task-specific prompts.

Classification Few-Shot Learning +6

KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering

1 code implementation6 May 2022 Jianing Wang, Chengyu Wang, Minghui Qiu, Qiuhui Shi, Hongbin Wang, Jun Huang, Ming Gao

Extractive Question Answering (EQA) is one of the most important tasks in Machine Reading Comprehension (MRC), which can be solved by fine-tuning the span selecting heads of Pre-trained Language Models (PLMs).

Contrastive Learning Extractive Question-Answering +5

Making Pre-trained Language Models End-to-end Few-shot Learners with Contrastive Prompt Tuning

1 code implementation1 Apr 2022 Ziyun Xu, Chengyu Wang, Minghui Qiu, Fuli Luo, Runxin Xu, Songfang Huang, Jun Huang

Pre-trained Language Models (PLMs) have achieved remarkable performance for various language understanding tasks in IR systems, which require the fine-tuning process based on labeled training data.

Contrastive Learning

HiCLRE: A Hierarchical Contrastive Learning Framework for Distantly Supervised Relation Extraction

1 code implementation Findings (ACL) 2022 Dongyang Li, Taolin Zhang, Nan Hu, Chengyu Wang, Xiaofeng He

In this paper, we propose a hierarchical contrastive learning Framework for Distantly Supervised relation extraction (HiCLRE) to reduce noisy sentences, which integrate the global structural information and local fine-grained interaction.

Contrastive Learning Data Augmentation +1

From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression

2 code implementations14 Dec 2021 Runxin Xu, Fuli Luo, Chengyu Wang, Baobao Chang, Jun Huang, Songfang Huang, Fei Huang

Unified in contrastive learning, CAP enables the pruned model to learn from the pre-trained model for task-agnostic knowledge, and fine-tuned model for task-specific knowledge.

Contrastive Learning Language Modelling +2

DKPLM: Decomposable Knowledge-enhanced Pre-trained Language Model for Natural Language Understanding

1 code implementation2 Dec 2021 Taolin Zhang, Chengyu Wang, Nan Hu, Minghui Qiu, Chengguang Tang, Xiaofeng He, Jun Huang

Knowledge-Enhanced Pre-trained Language Models (KEPLMs) are pre-trained models with relation triples injecting from knowledge graphs to improve language understanding abilities.

Knowledge Graphs Knowledge Probing +3

INTERN: A New Learning Paradigm Towards General Vision

no code implementations16 Nov 2021 Jing Shao, Siyu Chen, Yangguang Li, Kun Wang, Zhenfei Yin, Yinan He, Jianing Teng, Qinghong Sun, Mengya Gao, Jihao Liu, Gengshi Huang, Guanglu Song, Yichao Wu, Yuming Huang, Fenggang Liu, Huan Peng, Shuo Qin, Chengyu Wang, Yujie Wang, Conghui He, Ding Liang, Yu Liu, Fengwei Yu, Junjie Yan, Dahua Lin, Xiaogang Wang, Yu Qiao

Enormous waves of technological innovations over the past several years, marked by the advances in AI technologies, are profoundly reshaping the industry and the society.

Snapshot Ptychography on Array cameras

1 code implementation5 Nov 2021 Chengyu Wang, Minghao Hu, Yuzuru Takashima, Timothy J. Schulz, David J. Brady

We use convolutional neural networks to recover images optically down-sampled by $6. 7\times$ using coherent aperture synthesis over a 16 camera array.

Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings

no code implementations29 Oct 2021 Guanglin Niu, Yang Li, Chengguang Tang, Zhongkai Hu, Shibin Yang, Peng Li, Chengyu Wang, Hao Wang, Jian Sun

The multi-relational Knowledge Base Question Answering (KBQA) system performs multi-hop reasoning over the knowledge graph (KG) to achieve the answer.

Knowledge Base Question Answering Knowledge Graph Embedding +1

SMedBERT: A Knowledge-Enhanced Pre-trained Language Model with Structured Semantics for Medical Text Mining

2 code implementations ACL 2021 Taolin Zhang, Zerui Cai, Chengyu Wang, Minghui Qiu, Bite Yang, Xiaofeng He

Recently, the performance of Pre-trained Language Models (PLMs) has been significantly improved by injecting knowledge facts to enhance their abilities of language understanding.

Language Modelling Natural Language Inference +1

Multiscale Phase Retrieval

1 code implementation9 Dec 2020 David J. Brady, Timothy J. Schulz, Chengyu Wang

Phase-sensitive sensor planes using such devices could eliminate the need both for lenses and reference signals, creating a path to large aperture diffraction limited laser imaging.

Retrieval

Learning to Expand: Reinforced Pseudo-relevance Feedback Selection for Information-seeking Conversations

no code implementations25 Nov 2020 Haojie Pan, Cen Chen, Chengyu Wang, Minghui Qiu, Liu Yang, Feng Ji, Jun Huang

More specifically, we propose a reinforced selector to extract useful PRF terms to enhance response candidates and a BERT-based response ranker to rank the PRF-enhanced responses.

EasyTransfer -- A Simple and Scalable Deep Transfer Learning Platform for NLP Applications

2 code implementations18 Nov 2020 Minghui Qiu, Peng Li, Chengyu Wang, Hanjie Pan, Ang Wang, Cen Chen, Xianyan Jia, Yaliang Li, Jun Huang, Deng Cai, Wei Lin

The literature has witnessed the success of leveraging Pre-trained Language Models (PLMs) and Transfer Learning (TL) algorithms to a wide range of Natural Language Processing (NLP) applications, yet it is not easy to build an easy-to-use and scalable TL toolkit for this purpose.

Conversational Question Answering Transfer Learning

EasyASR: A Distributed Machine Learning Platform for End-to-end Automatic Speech Recognition

no code implementations14 Sep 2020 Chengyu Wang, Mengli Cheng, Xu Hu, Jun Huang

We present EasyASR, a distributed machine learning platform for training and serving large-scale Automatic Speech Recognition (ASR) models, as well as collecting and processing audio data at scale.

Automatic Speech Recognition BIG-bench Machine Learning +1

Knowledge-Empowered Representation Learning for Chinese Medical Reading Comprehension: Task, Model and Resources

1 code implementation Findings (ACL) 2021 Taolin Zhang, Chengyu Wang, Minghui Qiu, Bite Yang, Xiaofeng He, Jun Huang

In this paper, we introduce a multi-target MRC task for the medical domain, whose goal is to predict answers to medical questions and the corresponding support sentences from medical information sources simultaneously, in order to ensure the high reliability of medical knowledge serving.

Machine Reading Comprehension Multi-Task Learning +1

Weakly Supervised Construction of ASR Systems with Massive Video Data

no code implementations4 Aug 2020 Mengli Cheng, Chengyu Wang, Xu Hu, Jun Huang, Xiaobo Wang

Building Automatic Speech Recognition (ASR) systems from scratch is significantly challenging, mostly due to the time-consuming and financially-expensive process of annotating a large amount of audio data with transcripts.

Automatic Speech Recognition Optical Character Recognition +2

Meta Fine-Tuning Neural Language Models for Multi-Domain Text Mining

2 code implementations EMNLP 2020 Chengyu Wang, Minghui Qiu, Jun Huang, Xiaofeng He

In this paper, we propose an effective learning procedure named Meta Fine-Tuning (MFT), served as a meta-learner to solve a group of similar NLP tasks for neural language models.

Few-Shot Learning Language Modelling

KEML: A Knowledge-Enriched Meta-Learning Framework for Lexical Relation Classification

no code implementations25 Feb 2020 Chengyu Wang, Minghui Qiu, Jun Huang, Xiaofeng He

We further combine a meta-learning process over the auxiliary task distribution and supervised learning to train the neural lexical relation classifier.

General Classification Meta-Learning +1

Population pharmacokinetics and dosing regimen optimization of tacrolimus in Chinese lung transplant recipients

no code implementations1 Feb 2020 Xiaojun Cai, Huizhu Song, Zheng Jiao, Hang Yang, Min Zhu, Chengyu Wang, Dong Wei, Lingzhi Shi, Bo Wu, Jinyu Chen

Given the nonlinear kinetics of tacrolimus and large variability, population pharmacokinetic model should be combined with therapeutic drug monitoring to optimize individualized therapy.

Video Generation from Single Semantic Label Map

2 code implementations CVPR 2019 Junting Pan, Chengyu Wang, Xu Jia, Jing Shao, Lu Sheng, Junjie Yan, Xiaogang Wang

This paper proposes the novel task of video generation conditioned on a SINGLE semantic label map, which provides a good balance between flexibility and quality in the generation process.

Image Generation Image to Video Generation +1

Learning Fine-grained Relations from Chinese User Generated Categories

no code implementations EMNLP 2017 Chengyu Wang, Yan Fan, Xiaofeng He, Aoying Zhou

User generated categories (UGCs) are short texts that reflect how people describe and organize entities, expressing rich semantic relations implicitly.

Graph Mining Relation Extraction

Transductive Non-linear Learning for Chinese Hypernym Prediction

no code implementations ACL 2017 Chengyu Wang, Junchi Yan, Aoying Zhou, Xiaofeng He

Finding the correct hypernyms for entities is essential for taxonomy learning, fine-grained entity categorization, query understanding, etc.

Relation Extraction Transductive Learning

Chinese Hypernym-Hyponym Extraction from User Generated Categories

no code implementations COLING 2016 Chengyu Wang, Xiaofeng He

Hypernym-hyponym ({``}is-a{''}) relations are key components in taxonomies, object hierarchies and knowledge graphs.

Knowledge Graphs Machine Translation +4

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