Rui Zhang

A research on identification method for WiFi-based home automation device suites

2017

WiFi communication is widely used in home automation. In order to identify home automation device suites from the complex network environment, we employ Bi-flow model based on WiFi traffic model and combine the analysis of …

Neural Relation Extraction for Knowledge Base Enrichment

2019

We study relation extraction for knowledge base (KB) enrichment. Specifically, we aim to extract entities and their relationships from sentences in the form of triples and map the elements of the extracted triples to an …

Surprise Languages: Rapid-Response Cross-Language IR

2019 · Edinburgh Research Explorer (University of Edinburgh)

Sixteen years ago, the first "surprise language exercise" was conducted, in Cebuano. The evaluation goal of a surprise language exercise is to learn how well systems for a new language can be quickly built. This …

Joint Recognition of Names and Publications in Academic Homepages

2020

Academic homepages are an important source for learning researchers' profiles. Recognising person names and publications in academic homepages are two fundamental tasks for understanding the identities of the homepages and collaboration networks of the researchers. …

Data User-Based Attribute-Based Encryption

2020 · arXiv (Cornell University)

Attribute-Based Encryption (ABE) has emerged as an information-centric public-key cryptographic system which allows a data owner to share data, according to access policy, with multiple data users based on the attributes they possess, without knowing …

Cross-language Sentence Selection via Data Augmentation and Rationale Training

2021 · arXiv (Cornell University)

This paper proposes an approach to cross-language sentence selection in a low-resource setting. It uses data augmentation and negative sampling techniques on noisy parallel sentence data to directly learn a cross-lingual embedding-based query relevance model. …

RAP: RAnsomware Protection Scheme Based on Blockchain

2022 · 2022 2nd International Conference on Consumer Electronics and Computer Engineering (ICCECE)

Ransomware attacks have caused serious data loss, and a frequent/good backup is the only solution to deal with such risks. Unfortunately, current research of data backup mainly focuses on improving data recovery efficiency, and rarely …

An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages

2022 · arXiv (Cornell University)

To provide click simulation or relevance estimation based on users' implicit interaction feedback, click models have been much studied during recent years. Most click models focus on user behaviors towards a single list. However, with …

Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems

2022 · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions. However, the cost of examining all the possible higher-order feature interactions is prohibitive (exponentially …

BARS

2022 · Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval

The past two decades have witnessed the rapid development of personalized recommendation techniques. Despite the significant progress made in both research and practice of recommender systems, to date, there is a lack of a widely-recognized …

Canine Parvovirus Diagnosis Classification Utilizing Veterinary Free-Text Notes

2022 · 2022 IEEE 10th International Conference on Healthcare Informatics (ICHI)

This work demonstrates a NLP pipeline on classifying different canine parvovirus diagnosis from visit summaries. The preliminary results show promising efficacy in employing BERT based models for this task. This work also reveals a way …

A Bird's-eye View of Reranking: from List Level to Page Level

2022 · arXiv (Cornell University)

Reranking, as the final stage of multi-stage recommender systems, refines the initial lists to maximize the total utility. With the development of multimedia and user interface design, the recommendation page has evolved to a multi-list …

PLM-GNN: A Webpage Classification Method based on Joint Pre-trained Language Model and Graph Neural Network

2023 · arXiv (Cornell University)

The number of web pages is growing at an exponential rate, accumulating massive amounts of data on the web. It is one of the key processes to classify webpages in web information mining. Some classical …

W-procer: Weighted Prototypical Contrastive Learning for Medical Few-Shot Named Entity Recognition

2023 · arXiv (Cornell University)

Contrastive learning has become a popular solution for few-shot Name Entity Recognization (NER). The conventional configuration strives to reduce the distance between tokens with the same labels and increase the distance between tokens with different …

<i>MHRR</i>: MOOCs Recommender Service With Meta Hierarchical Reinforced Ranking

2023 · IEEE Transactions on Services Computing

The exponential growth of Massive Open Online Courses (MOOCs) surges the needs of advanced models for personalized Online Education Services (OES). Existing solutions successfully recommend MOOCs courses via deep learning models, they however generate weak …

Locally Differentially Private and Fair Key-Value Aggregation

2023

In the era of Big Data, the ability to extract meaningful insights from vast datasets while maintaining individual privacy has become an increasingly complex challenge. Recent years have witnessed the development of various locally differentially …

Source-Free Active Domain Adaptation via Augmentation-Based Sample Query and Progressive Model Adaptation

2023 · IEEE Transactions on Neural Networks and Learning Systems

Active domain adaptation (ADA), which enormously improves the performance of unsupervised domain adaptation (UDA) at the expense of annotating limited target data, has attracted a surge of interest. However, in real-world applications, the source data …

MIGAN: A Privacy Leakage Evaluation Scheme for CIoT-Based Federated Learning Users

2024 · IEEE Transactions on Consumer Electronics

Federated Learning (FL) in Consumer Internet of Things (CIoT) encounters significant privacy security threats when collaborative training Machine Learning models using data distributed among numerous smart CIoT devices. This paper’s objective is to evaluate the …

An Anchor Learning Approach for Citation Field Learning

2024

Citation field learning is to segment a citation string into fields of interest such as author, title, and venue. Extracting such fields from citations is crucial for citation indexing, researcher profile analysis, etc. User-generated resources …

Generation is better than Modification: Combating High Class Homophily Variance in Graph Anomaly Detection

2024 · arXiv (Cornell University)

Graph-based anomaly detection is currently an important research topic in the field of graph neural networks (GNNs). We find that in graph anomaly detection, the homophily distribution differences between different classes are significantly greater than …

Cancellation in sums over special sequences on $\mathbf{\rm{GL}_{m}}$ and their applications

2024 · arXiv (Cornell University)

Let $a(n)$ be the $n$-th Dirichlet coefficient of the automorphic $L$-function or the Rankin--Selberg $L$-function. We investigate the cancellation of $a(n)$ over sequences linked to the Waring--Goldbach problem, by establishing a nontrivial bound for the …

RAMIE: Retrieval-Augmented Multi-task Information Extraction with Large Language Models on Dietary Supplements

2024 · arXiv (Cornell University)

\textbf{Objective:} We aimed to develop an advanced multi-task large language model (LLM) framework to extract multiple types of information about dietary supplements (DS) from clinical records. \textbf{Methods:} We used four core DS information extraction tasks …

Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning

2025

Foundation models that bridge vision and language have made significant progress. While they have inspired many life-enriching applications, their potential for abuse in creating new threats remains largely unexplored. In this paper, we reveal that …

Large Language Models for Mathematical Reasoning: Progresses and Challenges

2024

Janice Ahn, Rishu Verma, Renze Lou, Di Liu, Rui Zhang, Wenpeng Yin. Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop. 2024.

External Large Foundation Model: How to Efficiently Serve Trillions of Parameters for Online Ads Recommendation

2025 · arXiv (Cornell University)

Ads recommendation is a prominent service of online advertising systems and has been actively studied. Recent studies indicate that scaling-up and advanced design of the recommendation model can bring significant performance improvement. However, with a …

Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task

2018

Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, Dragomir Radev. Proceedings of the 2018 Conference on Empirical Methods in Natural Language …

Graph-based Neural Multi-Document Summarization

2017

We propose a neural multi-document summarization (MDS) system that incorporates sentence relation graphs. We employ a Graph Convolutional Network (GCN) on the relation graphs, with sentence embeddings obtained from Recurrent Neural Networks as input node …

CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databases

2019

Tao Yu, Rui Zhang, Heyang Er, Suyi Li, Eric Xue, Bo Pang, Xi Victoria Lin, Yi Chern Tan, Tianze Shi, Zihan Li, Youxuan Jiang, Michihiro Yasunaga, Sungrok Shim, Tao Chen, Alexander Fabbri, Zifan Li, Luyao …

ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks

2019 · Proceedings of the AAAI Conference on Artificial Intelligence

Scientific article summarization is challenging: large, annotated corpora are not available, and the summary should ideally include the article’s impacts on research community. This paper provides novel solutions to these two challenges. We 1) develop …

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models

2022

Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir …