Jie Liu

Distributed Searchable Asymmetric Encryption

2016 · Indonesian Journal of Electrical Engineering and Computer Science

<p><em>Searchable asymmetric encryption (SAE) can also be called Public Key Encryption with Keyword Search (PEKS), which allows us to search the keyword on the data of having been encrypted. The essence of Asymmetric searchable encryption …

Techniques for Efficiently Handling Power Surges in Fuel Cell Powered Data Centers: Modeling, Analysis, Results

2018 · arXiv (Cornell University)

Fuel cells are a promising power source for future data centers, offering high energy efficiency, low greenhouse gas emissions, and high reliability. However, due to mechanical limitations related to fuel delivery, fuel cells are slow …

Learning Multi-Graph Neural Network for Data-Driven Job Skill Prediction

2021

Specifying an appropriate skill set for a job position is critical for talent recruitment. However, it is often more difficult than people think since it needs a great understanding of the role of the position, …

A Natural Language Instruction Disambiguation Method for Robot Grasping

2021 · 2021 IEEE International Conference on Robotics and Biomimetics (ROBIO)

Robot grasping under the instruction of natural language has attracted increasing attention in various applications for its advantages in enabling natural and smooth human-robot interaction. At present, mainstream algorithms mainly solve problems of utilizing simple …

A GPU-specialized Inference Parameter Server for Large-Scale Deep Recommendation Models

2022

Recommendation systems are of crucial importance for a variety of modern apps and web services, such as news feeds, social networks, e-commerce, search, etc. To achieve peak prediction accuracy, modern recommendation models combine deep learning …

Autoencoder-based OFDM for Agricultural Image Transmission

2022

With the rapid development of the Internet of Things (IoT), smart agricultural puts forward higher demands on the transmission of agricultural big data. This paper proposes an end-to-end learning communication with autoencoder-based orthogonal frequency division …

An Empirical Study of Uniform-Architecture Knowledge Distillation in Document Ranking

2023 · arXiv (Cornell University)

Although BERT-based ranking models have been commonly used in commercial search engines, they are usually time-consuming for online ranking tasks. Knowledge distillation, which aims at learning a smaller model with comparable performance to a larger …

ESCL: Equivariant Self-Contrastive Learning for Sentence Representations

2023

Previous contrastive learning methods for sentence representations often focus on insensitive transformations to produce positive pairs, but neglect the role of sensitive transformations that are harmful to semantic representations. Therefore, we propose an Equivariant Self-Contrastive …

Norm-Range Partition: A Universal Catalyst for LSH based Maximum Inner Product Search (MIPS)

2018 · arXiv (Cornell University)

Recently, locality sensitive hashing (LSH) was shown to be effective for MIPS and several algorithms including $L_2$-ALSH, Sign-ALSH and Simple-LSH have been proposed. In this paper, we introduce the norm-range partition technique, which partitions the …

Anomaly Multi-classification in Industrial Scenarios: Transferring Few-shot Learning to a New Task

2024 · arXiv (Cornell University)

In industrial scenarios, it is crucial not only to identify anomalous items but also to classify the type of anomaly. However, research on anomaly multi-classification remains largely unexplored. This paper proposes a novel and valuable …

GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models

2024

Shilong Li, Yancheng He, Hangyu Guo, Xingyuan Bu, Ge Bai, Jie Liu, Jiaheng Liu, Xingwei Qu, Yangguang Li, Wanli Ouyang, Wenbo Su, Bo Zheng. Findings of the Association for Computational Linguistics: EMNLP 2024. 2024.

Research Progress of Knowledge Graph and Attention Mechanism in Recommender Systems

2025

With the development of the Internet and the explosive expansion of information volume, it becomes arduous for users to make a choice in the face of overwhelming information. This makes the recommendation system an effective …

AgentDropout: Dynamic Agent Elimination for Token-Efficient and High-Performance LLM-Based Multi-Agent Collaboration

2025

Multi-agent systems (MAS) based on large language models (LLMs) have demonstrated significant potential in collaborative problemsolving.However, they still face substantial challenges of low communication efficiency and suboptimal task performance, making the careful design of the …