Search Results for author:
Found 6 papers, 2 papers with code
CogTaskonomy: Cognitively Inspired Task Taxonomy Is Beneficial to Transfer Learning in NLP
Is there a principle to guide transfer learning across tasks in natural language processing (NLP)?
Modeling Unified Semantic Discourse Structure for High-quality Headline Generation
To consolidate the efficacy of S3 graphs, we further devise a hierarchical structure pruning mechanism to dynamically screen the redundant and nonessential nodes within the graph.
FedRFQ: Prototype-Based Federated Learning with Reduced Redundancy, Minimal Failure, and Enhanced Quality
Federated learning is a powerful technique that enables collaborative learning among different clients.
DEPN: Detecting and Editing Privacy Neurons in Pretrained Language Models
The ability of data memorization and regurgitation in pretrained language models, revealed in previous studies, brings the risk of data leakage.
Incentive Mechanism Design for Joint Resource Allocation in Blockchain-based Federated Learning
Since each client has a limited amount of computing resources, the problem of allocating computing resources into training and mining needs to be carefully addressed.
Blockchain and Federated Edge Learning for Privacy-Preserving Mobile Crowdsensing
Mobile crowdsensing (MCS) counting on the mobility of massive workers helps the requestor accomplish various sensing tasks with more flexibility and lower cost.
