b'Ming Zhong'

research

∙ 09/01/2023

Towards a "Swiss Army Knife" for Scalable User-Defined Temporal (k,𝒳)-Core Analysis

Querying cohesive subgraphs on temporal graphs (e.g., social network, fi...

0 Ming Zhong, et al. ∙

research

∙ 07/19/2023

Towards Saner Deep Image Registration

With recent advances in computing hardware and surges of deep-learning a...

0 Bin Duan, et al. ∙

research

∙ 07/08/2023

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

Most existing cross-lingual summarization (CLS) work constructs CLS corp...

0 Yulong Chen, et al. ∙

research

∙ 07/04/2023

ReactIE: Enhancing Chemical Reaction Extraction with Weak Supervision

Structured chemical reaction information plays a vital role for chemists...

0 Ming Zhong, et al. ∙

research

∙ 06/11/2023

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

Emotion recognition in conversation, which aims to predict the emotion f...

0 Ting Zhang, et al. ∙

research

∙ 05/23/2023

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

Instruction tuning has emerged to enhance the capabilities of large lang...

0 Da Yin, et al. ∙

research

∙ 01/10/2023

Scalable Time-Range k-Core Query on Temporal Graphs(Full Version)

Querying cohesive subgraphs on temporal graphs with various time constra...

0 Junyong Yang, et al. ∙

research

∙ 11/03/2022

Open-Vocabulary Argument Role Prediction for Event Extraction

The argument role in event extraction refers to the relation between an ...

0 Yizhu Jiao, et al. ∙

research

∙ 09/29/2022

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

Traditional training paradigms for extractive and abstractive summarizat...

0 Chenxin An, et al. ∙

research

∙ 08/04/2022

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

Dynamical systems across many disciplines are modeled as interacting par...

22 Jinchao Feng, et al. ∙

research

∙ 07/13/2022

Grassmanian packings: Trust region stochastic tuning for matrix incoherence

We provide a new numerical procedure for constructing low coherence matr...

0 Josiah Park, et al. ∙

research

∙ 05/12/2022

CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation

Scientific extreme summarization (TLDR) aims to form ultra-short summari...

0 Yuning Mao, et al. ∙

research

∙ 05/01/2022

The Cross-lingual Conversation Summarization Challenge

We propose the shared task of cross-lingual conversation summarization, ...

0 Yulong Chen, et al. ∙

research

∙ 09/16/2021

RetrievalSum: A Retrieval Enhanced Framework for Abstractive Summarization

Existing summarization systems mostly generate summaries purely relying ...

0 Chenxin An, et al. ∙

research

∙ 08/26/2021

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

Building accurate and predictive models of the underlying mechanisms of ...

0 Ming Zhong, et al. ∙

research

∙ 06/18/2021

GEM: A General Evaluation Benchmark for Multimodal Tasks

In this paper, we present GEM as a General Evaluation benchmark for Mult...

0 Lin Su, et al. ∙

research

∙ 05/29/2021

Examiner: Automatically Locating Inconsistent Instructions Between Real Devices and CPU Emulators for ARM

Emulator is widely used to build dynamic analysis frameworks due to its ...

0 Muhui Jiang, et al. ∙

research

∙ 04/23/2021

Becoming Good at AI for Good

AI for good (AI4G) projects involve developing and applying artificial i...

0 Meghana Kshirsagar, et al. ∙

research

∙ 04/18/2021

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

Video-text retrieval plays an essential role in multi-modal research and...

0 Huaishao Luo, et al. ∙

research

∙ 04/07/2021

Enhancing Scientific Papers Summarization with Citation Graph

Previous work for text summarization in scientific domain mainly focused...

0 Chenxin An, et al. ∙

research

∙ 03/29/2021

Dynamic Network Embedding Survey

Since many real world networks are evolving over time, such as social ne...

0 Guotong Xue, et al. ∙

research

∙ 01/30/2021

Learning Interaction Kernels for Agent Systems on Riemannian Manifolds

Interacting agent and particle systems are extensively used to model com...

0 Mauro Maggioni, et al. ∙

research

∙ 10/11/2020

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

Neural network-based models augmented with unsupervised pre-trained know...

0 Yiran Chen, et al. ∙

research

∙ 10/08/2020

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

Modeling the complex interactions of systems of particles or agents is a...

17 Jason Miller, et al. ∙

research

∙ 04/19/2020

Extractive Summarization as Text Matching

This paper creates a paradigm shift with regard to the way we build neur...

0 Ming Zhong, et al. ∙

research

∙ 04/09/2020

Sparse recovery of noisy data using the Lasso method

We present a detailed analysis of the unconstrained ℓ_1-method Lasso met...

0 Eitan Tadmor, et al. ∙

research

∙ 04/09/2020

Sparse recovery of noisy data and Grothendieck inequality

We present a detailed analysis of the unconstrained ℓ_1-method LASSO for...

0 Eitan Tadmor, et al. ∙

research

∙ 12/23/2019

Data-driven Discovery of Emergent Behaviors in Collective Dynamics

Particle- and agent-based systems are a ubiquitous modeling tool in many...

15 Mauro Maggioni, et al. ∙

research

∙ 09/30/2019

A Closer Look at Data Bias in Neural Extractive Summarization Models

In this paper, we take stock of the current state of summarization datas...

0 Ming Zhong, et al. ∙

research

∙ 09/28/2019

GDP: Generalized Device Placement for Dataflow Graphs

Runtime and scalability of large neural networks can be significantly af...

0 Yanqi Zhou, et al. ∙

research

∙ 08/30/2019

Exploring Domain Shift in Extractive Text Summarization

Although domain shift has been well explored in many NLP applications, i...

0 Danqing Wang, et al. ∙

research

∙ 07/08/2019

Searching for Effective Neural Extractive Summarization: What Works and What's Next

The recent years have seen remarkable success in the use of deep neural ...

0 Ming Zhong, et al. ∙

research

∙ 12/14/2018

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

Inferring the laws of interaction between particles and agents in comple...

0 Fei Lu, et al. ∙

research

∙ 02/01/2015

Feature Selection with Redundancy-complementariness Dispersion

Feature selection has attracted significant attention in data mining and...

0 Zhijun Chen, et al. ∙

Ming Zhong

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