Search Results for author: Jingwei Yi

Found 7 papers, 5 papers with code

Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark

1 code implementation17 May 2023 Wenjun Peng, Jingwei Yi, Fangzhao Wu, Shangxi Wu, Bin Zhu, Lingjuan Lyu, Binxing Jiao, Tong Xu, Guangzhong Sun, Xing Xie

Companies have begun to offer Embedding as a Service (EaaS) based on these LLMs, which can benefit various natural language processing (NLP) tasks for customers.

Model extraction

Effective and Efficient Query-aware Snippet Extraction for Web Search

1 code implementation17 Oct 2022 Jingwei Yi, Fangzhao Wu, Chuhan Wu, Xiaolong Huang, Binxing Jiao, Guangzhong Sun, Xing Xie

In this paper, we propose an effective query-aware webpage snippet extraction method named DeepQSE, aiming to select a few sentences which can best summarize the webpage content in the context of input query.

Robust Quantity-Aware Aggregation for Federated Learning

no code implementations22 May 2022 Jingwei Yi, Fangzhao Wu, Huishuai Zhang, Bin Zhu, Tao Qi, Guangzhong Sun, Xing Xie

Federated learning (FL) enables multiple clients to collaboratively train models without sharing their local data, and becomes an important privacy-preserving machine learning framework.

Federated Learning Privacy Preserving

UA-FedRec: Untargeted Attack on Federated News Recommendation

1 code implementation14 Feb 2022 Jingwei Yi, Fangzhao Wu, Bin Zhu, Yang Yu, Chao Zhang, Guangzhong Sun, Xing Xie

Our study reveals a critical security issue in existing federated news recommendation systems and calls for research efforts to address the issue.

Federated Learning News Recommendation +2

Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation

1 code implementation2 Dec 2021 Yang Yu, Fangzhao Wu, Chuhan Wu, Jingwei Yi, Qi Liu

We further propose a two-stage knowledge distillation method to improve the efficiency of the large PLM-based news recommendation model while maintaining its performance.

Knowledge Distillation Natural Language Understanding +1

Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation

1 code implementation EMNLP 2021 Jingwei Yi, Fangzhao Wu, Chuhan Wu, Ruixuan Liu, Guangzhong Sun, Xing Xie

However, the computation and communication cost of directly learning many existing news recommendation models in a federated way are unacceptable for user clients.

Federated Learning News Recommendation +1

DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation

no code implementations15 Apr 2021 Jingwei Yi, Fangzhao Wu, Chuhan Wu, Qifei Li, Guangzhong Sun, Xing Xie

The core of our method includes a bias representation module, a bias-aware user modeling module, and a bias-aware click prediction module.

News Recommendation

Cannot find the paper you are looking for? You can Submit a new open access paper.