Search Results for author: Ming Zhong

Found 25 papers, 12 papers with code

PREME: Preference-based Meeting Exploration through an Interactive Questionnaire

no code implementations5 May 2022 Negar Arabzadeh, Ali Ahmadvand, Julia Kiseleva, Yang Liu, Ahmed Hassan Awadallah, Ming Zhong, Milad Shokouhi

The recent increase in the volume of online meetings necessitates automated tools for managing and organizing the material, especially when an attendee has missed the discussion and needs assistance in quickly exploring it.

The Cross-lingual Conversation Summarization Challenge

no code implementations1 May 2022 Yulong Chen, Ming Zhong, Xuefeng Bai, Naihao Deng, Jing Li, Xianchao Zhu, Yue Zhang

We propose the shared task of cross-lingual conversation summarization, \emph{ConvSumX Challenge}, opening new avenues for researchers to investigate solutions that integrate conversation summarization and machine translation.

Machine Translation Translation

Unsupervised Summarization with Customized Granularities

no code implementations29 Jan 2022 Ming Zhong, Yang Liu, Suyu Ge, Yuning Mao, Yizhu Jiao, Xingxing Zhang, Yichong Xu, Chenguang Zhu, Michael Zeng, Jiawei Han

We take events as the basic semantic units of the source documents and propose to rank these events by their salience.

Abstractive Text Summarization

An Improved Composite Functional Gradient Learning by Wasserstein Regularization for Generative adversarial networks

no code implementations29 Sep 2021 Chang Wan, Yanwei Fu, Ke Fan, Jinshan Zeng, Ming Zhong, Riheng Jia, MingLu Li, ZhongLong Zheng

However, the discriminator using logistic regression from the CFG framework is gradually hard to discriminate between real and fake images while the training steps go on.

Image Generation

RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

no code implementations16 Sep 2021 Chenxin An, Ming Zhong, Zhichao Geng, Jianqiang Yang, Xipeng Qiu

Existing summarization systems mostly generate summaries purely relying on the content of the source document.

Abstractive Text Summarization

DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization

1 code implementation6 Sep 2021 Ming Zhong, Yang Liu, Yichong Xu, Chenguang Zhu, Michael Zeng

For a dialogue, it corrupts a window of text with dialogue-inspired noise, and guides the model to reconstruct this window based on the content of the remaining conversation.

abstractive question answering Denoising +2

Machine Learning for Discovering Effective Interaction Kernels between Celestial Bodies from Ephemerides

no code implementations26 Aug 2021 Ming Zhong, Jason Miller, Mauro Maggioni

Building accurate and predictive models of the underlying mechanisms of celestial motion has inspired fundamental developments in theoretical physics.

GEM: A General Evaluation Benchmark for Multimodal Tasks

1 code implementation Findings (ACL) 2021 Lin Su, Nan Duan, Edward Cui, Lei Ji, Chenfei Wu, Huaishao Luo, Yongfei Liu, Ming Zhong, Taroon Bharti, Arun Sacheti

Comparing with existing multimodal datasets such as MSCOCO and Flicker30K for image-language tasks, YouCook2 and MSR-VTT for video-language tasks, GEM is not only the largest vision-language dataset covering image-language tasks and video-language tasks at the same time, but also labeled in multiple languages.

CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval

3 code implementations18 Apr 2021 Huaishao Luo, Lei Ji, Ming Zhong, Yang Chen, Wen Lei, Nan Duan, Tianrui Li

In this paper, we propose a CLIP4Clip model to transfer the knowledge of the CLIP model to video-language retrieval in an end-to-end manner.

Video-Text Retrieval Video Understanding

QMSum: A New Benchmark for Query-based Multi-domain Meeting Summarization

1 code implementation NAACL 2021 Ming Zhong, Da Yin, Tao Yu, Ahmad Zaidi, Mutethia Mutuma, Rahul Jha, Ahmed Hassan Awadallah, Asli Celikyilmaz, Yang Liu, Xipeng Qiu, Dragomir Radev

As increasing numbers of meetings are recorded and transcribed, meeting summaries have become essential to remind those who may or may not have attended the meetings about the key decisions made and the tasks to be completed.

Meeting Summarization

Enhancing Scientific Papers Summarization with Citation Graph

1 code implementation7 Apr 2021 Chenxin An, Ming Zhong, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang

Previous work for text summarization in scientific domain mainly focused on the content of the input document, but seldom considering its citation network.

Text Summarization

Dynamic Network Embedding Survey

no code implementations29 Mar 2021 Guotong Xue, Ming Zhong, JianXin Li, Jia Chen, Chengshuai Zhai, Ruochen Kong

Due to the lack of comprehensive investigation of them, we give a survey of dynamic network embedding in this paper.

Network Embedding

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds

no code implementations30 Jan 2021 Mauro Maggioni, Jason Miller, Hongda Qiu, Ming Zhong

Interacting agent and particle systems are extensively used to model complex phenomena in science and engineering.

CDEvalSumm: An Empirical Study of Cross-Dataset Evaluation for Neural Summarization Systems

2 code implementations Findings of the Association for Computational Linguistics 2020 Yiran Chen, PengFei Liu, Ming Zhong, Zi-Yi Dou, Danqing Wang, Xipeng Qiu, Xuanjing Huang

In this paper, we perform an in-depth analysis of characteristics of different datasets and investigate the performance of different summarization models under a cross-dataset setting, in which a summarizer trained on one corpus will be evaluated on a range of out-of-domain corpora.

Text Summarization

Learning Theory for Inferring Interaction Kernels in Second-Order Interacting Agent Systems

no code implementations8 Oct 2020 Jason Miller, Sui Tang, Ming Zhong, Mauro Maggioni

Modeling the complex interactions of systems of particles or agents is a fundamental scientific and mathematical problem that is studied in diverse fields, ranging from physics and biology, to economics and machine learning.

Learning Theory

Data-driven Discovery of Emergent Behaviors in Collective Dynamics

1 code implementation23 Dec 2019 Mauro Maggioni, Jason Miller, Ming Zhong

We consider the fundamental problem of inferring interaction kernels from observations of agent-based dynamical systems given observations of trajectories, in particular for collective dynamical systems exhibiting emergent behaviors with complicated interaction kernels, in a nonparametric fashion, and for kernels which are parametrized by a single unknown parameter.

A Closer Look at Data Bias in Neural Extractive Summarization Models

no code implementations WS 2019 Ming Zhong, Danqing Wang, PengFei Liu, Xipeng Qiu, Xuanjing Huang

In this paper, we take stock of the current state of summarization datasets and explore how different factors of datasets influence the generalization behaviour of neural extractive summarization models.

Extractive Summarization

GDP: Generalized Device Placement for Dataflow Graphs

no code implementations28 Sep 2019 Yanqi Zhou, Sudip Roy, Amirali Abdolrashidi, Daniel Wong, Peter C. Ma, Qiumin Xu, Ming Zhong, Hanxiao Liu, Anna Goldie, Azalia Mirhoseini, James Laudon

Runtime and scalability of large neural networks can be significantly affected by the placement of operations in their dataflow graphs on suitable devices.

Exploring Domain Shift in Extractive Text Summarization

no code implementations30 Aug 2019 Danqing Wang, PengFei Liu, Ming Zhong, Jie Fu, Xipeng Qiu, Xuanjing Huang

Although domain shift has been well explored in many NLP applications, it still has received little attention in the domain of extractive text summarization.

Extractive Text Summarization Meta-Learning

Nonparametric inference of interaction laws in systems of agents from trajectory data

1 code implementation14 Dec 2018 Fei Lu, Mauro Maggioni, Sui Tang, Ming Zhong

Inferring the laws of interaction between particles and agents in complex dynamical systems from observational data is a fundamental challenge in a wide variety of disciplines.

Feature Selection with Redundancy-complementariness Dispersion

no code implementations1 Feb 2015 Zhijun Chen, Chaozhong Wu, Yishi Zhang, Zhen Huang, Bin Ran, Ming Zhong, Nengchao Lyu

Feature selection has attracted significant attention in data mining and machine learning in the past decades.

General Classification

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