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Aoxiao Zhong

5 accepted papers

2025

LLM Agents for Education: Advances and Applications

EMNLP 2025

Large Language Model (LLM) agents are transforming education by automating complex pedagogical tasks and enhancing both teaching and learning processes. In this survey, we present a systematic review of recent advances in applying LLM agents to address key challenges in educational settings, such as

Cited by 0SourcePDFScholar
2023

An Empirical Analysis of Leveraging Knowledge for Low-Resource Task-Oriented Semantic Parsing

ACL 2023findings

Task-oriented semantic parsing has drawn a lot of interest from the NLP community, and especially the voice assistant industry as it enables representing the meaning of user requests with arbitrarily nested semantics, including multiple intents and compound entities. SOTA models are large seq2seq tr…

2023

FedDAR: Federated Domain-Aware Representation Learning

ICLR 2023poster

Cross-silo Federated learning (FL) has become a promising tool in machine learning applications for healthcare. It allows hospitals/institutions to train models with sufficient data while the data is kept private. To make sure the FL model is robust when facing heterogeneous data among FL clients, m…

2018

Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations

ICLR 2018workshop

Deep neural networks have become the state-of-the-art models in numerous machine learning tasks. However, general guidance to network architecture design is still missing. In our work, we bridge deep neural network design with numerical differential equations. We show that many effective networks, s…

Cited by 674SourceScholar
2018

Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations

ICML 2018oral

Deep neural networks have become the state-of-the-art models in numerous machine learning tasks. However, general guidance to network architecture design is still missing. In our work, we bridge deep neural network design with numerical differential equations. We show that many effective networks, s…