Search Results for author: Zixuan Zhang

Found 20 papers, 9 papers with code

COVID-19 Claim Radar: A Structured Claim Extraction and Tracking System

1 code implementation ACL 2022 Manling Li, Revanth Gangi Reddy, Ziqi Wang, Yi-shyuan Chiang, Tuan Lai, Pengfei Yu, Zixuan Zhang, Heng Ji

To tackle the challenge of accurate and timely communication regarding the COVID-19 pandemic, we present a COVID-19 Claim Radar to automatically extract supporting and refuting claims on a daily basis.

EventKE: Event-Enhanced Knowledge Graph Embedding

no code implementations Findings (EMNLP) 2021 Zixuan Zhang, Hongwei Wang, Han Zhao, Hanghang Tong, Heng Ji

Relations in most of the traditional knowledge graphs (KGs) only reflect static and factual connections, but fail to represent the dynamic activities and state changes about entities.

Knowledge Graph Embedding Knowledge Graphs +1

EVEDIT: Event-based Knowledge Editing with Deductive Editing Boundaries

no code implementations17 Feb 2024 Jiateng Liu, Pengfei Yu, Yuji Zhang, Sha Li, Zixuan Zhang, Heng Ji

The dynamic nature of real-world information necessitates efficient knowledge editing (KE) in large language models (LLMs) for knowledge updating.

knowledge editing

RESIN-EDITOR: A Schema-guided Hierarchical Event Graph Visualizer and Editor

1 code implementation5 Dec 2023 Khanh Duy Nguyen, Zixuan Zhang, Reece Suchocki, Sha Li, Martha Palmer, Susan Brown, Jiawei Han, Heng Ji

In this paper, we present RESIN-EDITOR, an interactive event graph visualizer and editor designed for analyzing complex events.

TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extraction

1 code implementation16 Nov 2023 Kuan-Hao Huang, I-Hung Hsu, Tanmay Parekh, Zhiyu Xie, Zixuan Zhang, Premkumar Natarajan, Kai-Wei Chang, Nanyun Peng, Heng Ji

In this work, we identify and address evaluation challenges, including inconsistency due to varying data assumptions or preprocessing steps, the insufficiency of current evaluation frameworks that may introduce dataset or data split bias, and the low reproducibility of some previous approaches.

Benchmarking Event Extraction

RigLSTM: Recurrent Independent Grid LSTM for Generalizable Sequence Learning

no code implementations3 Nov 2023 Ziyu Wang, Wenhao Jiang, Zixuan Zhang, Wei Tang, Junchi Yan

Sequential processes in real-world often carry a combination of simple subsystems that interact with each other in certain forms.

feature selection

Nonparametric Classification on Low Dimensional Manifolds using Overparameterized Convolutional Residual Networks

no code implementations4 Jul 2023 Kaiqi Zhang, Zixuan Zhang, Minshuo Chen, Yuma Takeda, Mengdi Wang, Tuo Zhao, Yu-Xiang Wang

Convolutional residual neural networks (ConvResNets), though overparameterized, can achieve remarkable prediction performance in practice, which cannot be well explained by conventional wisdom.

Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories

no code implementations26 Jun 2023 Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao

Existing theories on deep nonparametric regression have shown that when the input data lie on a low-dimensional manifold, deep neural networks can adapt to the intrinsic data structures.


Language Model Pre-Training with Sparse Latent Typing

1 code implementation23 Oct 2022 Liliang Ren, Zixuan Zhang, Han Wang, Clare R. Voss, ChengXiang Zhai, Heng Ji

Modern large-scale Pre-trained Language Models (PLMs) have achieved tremendous success on a wide range of downstream tasks.

Ranked #5 on Few-shot NER on Few-NERD (INTRA) (using extra training data)

Few-shot NER Language Modelling +1

Federated Reinforcement Learning for Real-Time Electric Vehicle Charging and Discharging Control

no code implementations4 Oct 2022 Zixuan Zhang, Yuning Jiang, Yuanming Shi, Ye Shi, Wei Chen

This paper develops an optimal EV charging/discharging control strategy for different EV users under dynamic environments to maximize EV users' benefits.

reinforcement-learning Reinforcement Learning (RL)

Schema-Guided Event Graph Completion

no code implementations6 Jun 2022 Hongwei Wang, Zixuan Zhang, Sha Li, Jiawei Han, Yizhou Sun, Hanghang Tong, Joseph P. Olive, Heng Ji

Existing link prediction or graph completion methods have difficulty dealing with event graphs because they are usually designed for a single large graph such as a social network or a knowledge graph, rather than multiple small dynamic event graphs.

Link Prediction

Sequential Information Design: Markov Persuasion Process and Its Efficient Reinforcement Learning

no code implementations22 Feb 2022 Jibang Wu, Zixuan Zhang, Zhe Feng, Zhaoran Wang, Zhuoran Yang, Michael I. Jordan, Haifeng Xu

This paper proposes a novel model of sequential information design, namely the Markov persuasion processes (MPPs), where a sender, with informational advantage, seeks to persuade a stream of myopic receivers to take actions that maximizes the sender's cumulative utilities in a finite horizon Markovian environment with varying prior and utility functions.

reinforcement-learning Reinforcement Learning (RL)

Fine-grained Information Extraction from Biomedical Literature based on Knowledge-enriched Abstract Meaning Representation

no code implementations ACL 2021 Zixuan Zhang, Nikolaus Parulian, Heng Ji, Ahmed Elsayed, Skatje Myers, Martha Palmer

In this paper, we propose a novel biomedical Information Extraction (IE) model to tackle these two challenges and extract scientific entities and events from English research papers.

Event Extraction Graph Attention +1

Abstract Meaning Representation Guided Graph Encoding and Decoding for Joint Information Extraction

1 code implementation NAACL 2021 Zixuan Zhang, Heng Ji

The tasks of Rich Semantic Parsing, such as Abstract Meaning Representation (AMR), share similar goals with Information Extraction (IE) to convert natural language texts into structured semantic representations.

Semantic Parsing

A State-Space Modeling Framework for Engineering Blockchain-Enabled Economic Systems

1 code implementation3 Jul 2018 Michael Zargham, Zixuan Zhang, Victor Preciado

Decentralized Ledger Technology, popularized by the Bitcoin network, aims to keep track of a ledger of valid transactions between agents of a virtual economy without a central institution for coordination.

Systems and Control Distributed, Parallel, and Cluster Computing

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