Search Results for author: Ming Zhong

Found 37 papers, 23 papers with code

L-Eval: Instituting Standardized Evaluation for Long Context Language Models

1 code implementation20 Jul 2023 Chenxin An, Shansan Gong, Ming Zhong, Mukai Li, Jun Zhang, Lingpeng Kong, Xipeng Qiu

Recently, there has been growing interest in extending the context length of instruction-following models in order to effectively process single-turn long input (e. g. summarizing a paper) and conversations with more extensive histories.

Instruction Following

Towards Saner Deep Image Registration

1 code implementation ICCV 2023 Bin Duan, Ming Zhong, Yan Yan

Moreover, we derive a set of theoretical guarantees for our sanity-checked image registration method, with experimental results supporting our theoretical findings and their effectiveness in increasing the sanity of models without sacrificing any performance.

Image Registration

Revisiting Cross-Lingual Summarization: A Corpus-based Study and A New Benchmark with Improved Annotation

1 code implementation8 Jul 2023 Yulong Chen, Huajian Zhang, Yijie Zhou, Xuefeng Bai, Yueguan Wang, Ming Zhong, Jianhao Yan, Yafu Li, Judy Li, Michael Zhu, Yue Zhang

Additionally, based on the same intuition, we propose a 2-Step method, which takes both conversation and summary as input to simulate human annotation process.

ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision

no code implementations4 Jul 2023 Ming Zhong, Siru Ouyang, Minhao Jiang, Vivian Hu, Yizhu Jiao, Xuan Wang, Jiawei Han

Structured chemical reaction information plays a vital role for chemists engaged in laboratory work and advanced endeavors such as computer-aided drug design.

Mimicking the Thinking Process for Emotion Recognition in Conversation with Prompts and Paraphrasing

1 code implementation11 Jun 2023 Ting Zhang, Zhuang Chen, Ming Zhong, Tieyun Qian

It is a challenging task since the recognition of the emotion in one utterance involves many complex factors, such as the conversational context, the speaker's background, and the subtle difference between emotion labels.

Emotion Recognition in Conversation

Dynosaur: A Dynamic Growth Paradigm for Instruction-Tuning Data Curation

1 code implementation23 May 2023 Da Yin, Xiao Liu, Fan Yin, Ming Zhong, Hritik Bansal, Jiawei Han, Kai-Wei Chang

As a novel continual learning scenario for instruction tuning, selecting tasks based on instruction representations can be an effective replaying strategy.

Continual Learning

Open-Vocabulary Argument Role Prediction for Event Extraction

1 code implementation3 Nov 2022 Yizhu Jiao, Sha Li, Yiqing Xie, Ming Zhong, Heng Ji, Jiawei Han

Specifically, we formulate the role prediction problem as an in-filling task and construct prompts for a pre-trained language model to generate candidate roles.

Event Extraction Language Modelling

Towards a Unified Multi-Dimensional Evaluator for Text Generation

1 code implementation13 Oct 2022 Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, PengFei Liu, Chenguang Zhu, Heng Ji, Jiawei Han

We re-frame NLG evaluation as a Boolean Question Answering (QA) task, and by guiding the model with different questions, we can use one evaluator to evaluate from multiple dimensions.

Question Answering Response Generation +3

COLO: A Contrastive Learning based Re-ranking Framework for One-Stage Summarization

1 code implementation COLING 2022 Chenxin An, Ming Zhong, Zhiyong Wu, Qin Zhu, Xuanjing Huang, Xipeng Qiu

Traditional training paradigms for extractive and abstractive summarization systems always only use token-level or sentence-level training objectives.

Abstractive Text Summarization Contrastive Learning +1

Data-driven soliton mappings for integrable fractional nonlinear wave equations via deep learning with Fourier neural operator

no code implementations29 Aug 2022 Ming Zhong, Zhenya Yan

The results obtained in this paper may be useful to further understand the neural networks in the fractional integrable nonlinear wave systems and the mappings between two spaces.

Learning Interaction Variables and Kernels from Observations of Agent-Based Systems

no code implementations4 Aug 2022 Jinchao Feng, Mauro Maggioni, Patrick Martin, Ming Zhong

Dynamical systems across many disciplines are modeled as interacting particles or agents, with interaction rules that depend on a very small number of variables (e. g. pairwise distances, pairwise differences of phases, etc...), functions of the state of pairs of agents.

Clustering Dimensionality Reduction

PREME: Preference-based Meeting Exploration through an Interactive Questionnaire

1 code implementation5 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

2 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.

Abstractive Dialogue Summarization Cross-Lingual Abstractive Summarization +3

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 regression

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.

BIG-bench Machine Learning

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

5 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.

Retrieval Text Retrieval +4

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.

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