Search Results for author:
Found 7 papers, 5 papers with code
Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark
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.
Effective and Efficient Query-aware Snippet Extraction for Web Search
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
Federated learning (FL) enables multiple clients to collaboratively train models without sharing their local data, and becomes an important privacy-preserving machine learning framework.
UA-FedRec: Untargeted Attack on Federated News Recommendation
Our study reveals a critical security issue in existing federated news recommendation systems and calls for research efforts to address the issue.
Tiny-NewsRec: Effective and Efficient PLM-based News Recommendation
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.
Efficient-FedRec: Efficient Federated Learning Framework for Privacy-Preserving News Recommendation
However, the computation and communication cost of directly learning many existing news recommendation models in a federated way are unacceptable for user clients.
DebiasedRec: Bias-aware User Modeling and Click Prediction for Personalized News Recommendation
The core of our method includes a bias representation module, a bias-aware user modeling module, and a bias-aware click prediction module.
