Search Results for author: Wei Ye

Found 39 papers, 18 papers with code

DESED: Dialogue-based Explanation for Sentence-level Event Detection

1 code implementation COLING 2022 Yinyi Wei, Shuaipeng Liu, Jianwei Lv, Xiangyu Xi, Hailei Yan, Wei Ye, Tong Mo, Fan Yang, Guanglu Wan

Many recent sentence-level event detection efforts focus on enriching sentence semantics, e. g., via multi-task or prompt-based learning.

Dialogue Generation Event Detection

Improving Embedding-based Large-scale Retrieval via Label Enhancement

no code implementations Findings (EMNLP) 2021 Peiyang Liu, Xi Wang, Sen Wang, Wei Ye, Xiangyu Xi, Shikun Zhang

Current embedding-based large-scale retrieval models are trained with 0-1 hard label that indicates whether a query is relevant to a document, ignoring rich information of the relevance degree.


Label Smoothing for Text Mining

no code implementations COLING 2022 Peiyang Liu, Xiangyu Xi, Wei Ye, Shikun Zhang

This paper presents a novel keyword-based LS method to automatically generate soft labels from hard labels via exploiting the relevance between labels and text instances.

Retrieval text-classification +2

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

1 code implementation22 Feb 2023 Jindong Wang, Xixu Hu, Wenxin Hou, Hao Chen, Runkai Zheng, Yidong Wang, Linyi Yang, Haojun Huang, Wei Ye, Xiubo Geng, Binxin Jiao, Yue Zhang, Xing Xie

In this paper, we conduct a thorough evaluation of the robustness of ChatGPT from the adversarial and out-of-distribution (OOD) perspective.

Adversarial Robustness Chatbot +1

Reviewing Labels: Label Graph Network with Top-k Prediction Set for Relation Extraction

no code implementations29 Dec 2022 Bo Li, Wei Ye, Jinglei Zhang, Shikun Zhang

Specifically, for a given sample, we build a label graph to review candidate labels in the Top-k prediction set and learn the connections between them.

Relation Extraction

Sequence Generation with Label Augmentation for Relation Extraction

1 code implementation29 Dec 2022 Bo Li, Dingyao Yu, Wei Ye, Jinglei Zhang, Shikun Zhang

Sequence generation demonstrates promising performance in recent information extraction efforts, by incorporating large-scale pre-trained Seq2Seq models.

Relation Extraction

MUSIED: A Benchmark for Event Detection from Multi-Source Heterogeneous Informal Texts

1 code implementation25 Nov 2022 Xiangyu Xi, Jianwei Lv, Shuaipeng Liu, Wei Ye, Fan Yang, Guanglu Wan

As a pioneering exploration that expands event detection to the scenarios involving informal and heterogeneous texts, we propose a new large-scale Chinese event detection dataset based on user reviews, text conversations, and phone conversations in a leading e-commerce platform for food service.

Event Detection

Museformer: Transformer with Fine- and Coarse-Grained Attention for Music Generation

1 code implementation19 Oct 2022 Botao Yu, Peiling Lu, Rui Wang, Wei Hu, Xu Tan, Wei Ye, Shikun Zhang, Tao Qin, Tie-Yan Liu

A recent trend is to use Transformer or its variants in music generation, which is, however, suboptimal, because the full attention cannot efficiently model the typically long music sequences (e. g., over 10, 000 tokens), and the existing models have shortcomings in generating musical repetition structures.

Music Generation

Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs

no code implementations COLING 2022 Zile Qiao, Wei Ye, Tong Zhang, Tong Mo, Weiping Li, Shikun Zhang

Answering natural language questions on knowledge graphs (KGQA) remains a great challenge in terms of understanding complex questions via multi-hop reasoning.

Answer Selection Knowledge Graphs +2

Conv-Adapter: Exploring Parameter Efficient Transfer Learning for ConvNets

no code implementations15 Aug 2022 Hao Chen, Ran Tao, Han Zhang, Yidong Wang, Wei Ye, Jindong Wang, Guosheng Hu, Marios Savvides

Beyond classification, Conv-Adapter can generalize to detection and segmentation tasks with more than 50% reduction of parameters but comparable performance to the traditional full fine-tuning.

Transfer Learning

Graph Kernels Based on Multi-scale Graph Embeddings

1 code implementation2 Jun 2022 Wei Ye, Hao Tian, Qijun Chen

To mitigate the two challenges, we propose a novel graph kernel called the Multi-scale Path-pattern Graph kernel (MPG), at the heart of which is the multi-scale path-pattern node feature map.

A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example

no code implementations13 May 2022 Xiangyu Xi, Chenxu Lv, Yuncheng Hua, Wei Ye, Chaobo Sun, Shuaipeng Liu, Fan Yang, Guanglu Wan

Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e. g., intents and slots); (ii) poor controllability and interpretability; (iii) annotation-hungry.

Chatbot Task-Oriented Dialogue Systems

Incorporating Heterophily into Graph Neural Networks for Graph Classification

1 code implementation15 Mar 2022 Wei Ye, Jiayi Yang, Sourav Medya, Ambuj Singh

Graph neural networks (GNNs) often assume strong homophily in graphs, seldom considering heterophily which means connected nodes tend to have different class labels and dissimilar features.

Graph Classification

Graph Neural Diffusion Networks for Semi-supervised Learning

1 code implementation24 Jan 2022 Wei Ye, Zexi Huang, Yunqi Hong, Ambuj Singh

To solve these two issues, we propose a new graph neural network called GND-Nets (for Graph Neural Diffusion Networks) that exploits the local and global neighborhood information of a vertex in a single layer.

Modeling Human-AI Team Decision Making

1 code implementation8 Jan 2022 Wei Ye, Francesco Bullo, Noah Friedkin, Ambuj K Singh

AI and humans bring complementary skills to group deliberations.

Decision Making

Frequency-Aware Contrastive Learning for Neural Machine Translation

no code implementations29 Dec 2021 Tong Zhang, Wei Ye, Baosong Yang, Long Zhang, Xingzhang Ren, Dayiheng Liu, Jinan Sun, Shikun Zhang, Haibo Zhang, Wen Zhao

Inspired by the observation that low-frequency words form a more compact embedding space, we tackle this challenge from a representation learning perspective.

Contrastive Learning Machine Translation +3

Temporally Consistent Online Depth Estimation in Dynamic Scenes

no code implementations17 Nov 2021 Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath

We present a framework named Consistent Online Dynamic Depth (CODD) to produce temporally consistent depth estimates in dynamic scenes in an online setting.

Stereo Depth Estimation

Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation

1 code implementation CVPR 2022 Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan

Therefore, we propose HRViT, which enhances ViTs to learn semantically-rich and spatially-precise multi-scale representations by integrating high-resolution multi-branch architectures with ViTs.

Image Classification Representation Learning +1

Deep Embedded K-Means Clustering

2 code implementations30 Sep 2021 Wengang Guo, Kaiyan Lin, Wei Ye

To this end, we discard the decoder and propose a greedy method to optimize the representation.

Deep Clustering Representation Learning

QuadrupletBERT: An Efficient Model For Embedding-Based Large-Scale Retrieval

no code implementations NAACL 2021 Peiyang Liu, Sen Wang, Xi Wang, Wei Ye, Shikun Zhang

The embedding-based large-scale query-document retrieval problem is a hot topic in the information retrieval (IR) field.

Information Retrieval Retrieval

Multi-Hop Transformer for Document-Level Machine Translation

no code implementations NAACL 2021 Long Zhang, Tong Zhang, Haibo Zhang, Baosong Yang, Wei Ye, Shikun Zhang

Document-level neural machine translation (NMT) has proven to be of profound value for its effectiveness on capturing contextual information.

Document Level Machine Translation Document Translation +3

Multi-view Inference for Relation Extraction with Uncertain Knowledge

1 code implementation28 Apr 2021 Bo Li, Wei Ye, Canming Huang, Shikun Zhang

Knowledge graphs (KGs) are widely used to facilitate relation extraction (RE) tasks.

Ranked #31 on Relation Extraction on DocRED (using extra training data)

Document-level Relation Extraction Knowledge Graphs

SongMASS: Automatic Song Writing with Pre-training and Alignment Constraint

1 code implementation9 Dec 2020 Zhonghao Sheng, Kaitao Song, Xu Tan, Yi Ren, Wei Ye, Shikun Zhang, Tao Qin

Automatic song writing aims to compose a song (lyric and/or melody) by machine, which is an interesting topic in both academia and industry.

Graph Enhanced Dual Attention Network for Document-Level Relation Extraction

no code implementations COLING 2020 Bo Li, Wei Ye, Zhonghao Sheng, Rui Xie, Xiangyu Xi, Shikun Zhang

Document-level relation extraction requires inter-sentence reasoning capabilities to capture local and global contextual information for multiple relational facts.

Document-level Relation Extraction

Learning Deep Graph Representations via Convolutional Neural Networks

1 code implementation5 Apr 2020 Wei Ye, Omid Askarisichani, Alex Jones, Ambuj Singh

The learned deep representation for a graph is a dense and low-dimensional vector that captures complex high-order interactions in a vertex neighborhood.

General Classification Graph Classification

Incorporating User's Preference into Attributed Graph Clustering

1 code implementation24 Mar 2020 Wei Ye, Dominik Mautz, Christian Boehm, Ambuj Singh, Claudia Plant

In contrast to global clustering, local clustering aims to find only one cluster that is concentrating on the given seed vertex (and also on the designated attributes for attributed graphs).

Graph Clustering

Leveraging Code Generation to Improve Code Retrieval and Summarization via Dual Learning

no code implementations24 Feb 2020 Wei Ye, Rui Xie, Jinglei Zhang, Tianxiang Hu, Xiaoyin Wang, Shikun Zhang

Since both tasks aim to model the association between natural language and programming language, recent studies have combined these two tasks to improve their performance.

Association Code Generation +4

Tree++: Truncated Tree Based Graph Kernels

1 code implementation23 Feb 2020 Wei Ye, Zhen Wang, Rachel Redberg, Ambuj Singh

At the heart of Tree++ is a graph kernel called the path-pattern graph kernel.

Graph Similarity

PKUSE at SemEval-2019 Task 3: Emotion Detection with Emotion-Oriented Neural Attention Network

no code implementations SEMEVAL 2019 Luyao Ma, Long Zhang, Wei Ye, Wenhui Hu

This paper presents the system in SemEval-2019 Task 3, {``}EmoContext: Contextual Emotion Detection in Text{''}.

Deep Dynamic Boosted Forest

no code implementations19 Apr 2018 Haixin Wang, Xingzhang Ren, Jinan Sun, Wei Ye, Long Chen, Muzhi Yu, Shikun Zhang

Specically, we propose to measure the quality of each leaf node of every decision tree in the random forest to determine hard examples.

Ensemble Learning

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