70 citations · 94 across the 6 of their papers we have counts for
6 papers
Integrating Reasoning and Generalization in Text-to-SQL via Self-Enhanced Fine-Tuning
Feng Lyu, Jinfeng Cen, Sijing Duan +4
Text-to-SQL aims to translate natural language questions into executable SQL queries over structured databases, enabling non-expert users to access data intuitively. While recent a…
Privacy-Preserving Federated Learning via Dataset Distillation
ShiMao Xu, Xiaopeng Ke, Xing Su +4
Federated Learning (FL) allows users to share knowledge instead of raw data to train a model with high accuracy. Unfortunately, during the training, users lose control over the kno…
CoAst: Validation-Free Contribution Assessment for Federated Learning based on Cross-Round Valuation
Hao Wu, Likun Zhang, Shucheng Li +2
In the federated learning (FL) process, since the data held by each participant is different, it is necessary to figure out which participant has a higher contribution to the model…
Self-supervised Incremental Deep Graph Learning for Ethereum Phishing Scam Detection
Shucheng Li, Fengyuan Xu, Runchuan Wang +1
In recent years, phishing scams have become the crime type with the largest money involved on Ethereum, the second-largest blockchain platform. Meanwhile, graph neural network (GNN…
Graph Neural Networks for Natural Language Processing: A Survey
Lingfei Wu, Yu Chen, Kai Shen +5
Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP). Although text inputs are typically represented as a sequence of tok…
Graph-to-Tree Neural Networks for Learning Structured Input-Output Translation with Applications to Semantic Parsing and Math Word Problem
Shucheng Li, Lingfei Wu, Shiwei Feng +3
The celebrated Seq2Seq technique and its numerous variants achieve excellent performance on many tasks such as neural machine translation, semantic parsing, and math word problem s…