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Yuanyuan Chen

7 accepted papers

2025

Can Textual Gradient Work in Federated Learning?

ICLR 2025poster

Recent studies highlight the promise of LLM-based prompt optimization, especially with TextGrad, which automates ``differentiation'' via texts and backpropagates textual feedback provided by LLMs. This approach facilitates training in various real-world applications that do not support numerical gra…

2024

Overcoming Catastrophic Forgetting by Exemplar Selection in Task-oriented Dialogue System

ACL 2024findings

Intelligent task-oriented dialogue systems (ToDs) are expected to continuously acquire new knowledge, also known as Continual Learning (CL), which is crucial to fit ever-changing user needs. However, catastrophic forgetting dramatically degrades the model performance in face of a long streamed curri…

Cited by 0SourcePDFScholar
2023

Efficient Training of Large-Scale Industrial Fault Diagnostic Models through Federated Opportunistic Block Dropout

AAAI 2023technical

Artificial intelligence (AI)-empowered industrial fault diagnostics is important in ensuring the safe operation of industrial applications. Since complex industrial systems often involve multiple industrial plants (possibly belonging to different companies or subsidiaries) with sensitive data collec…

Cited by 7SourcePDFScholar
2023

FedOBD: Opportunistic Block Dropout for Efficiently Training Large-scale Neural Networks through Federated Learning

IJCAI 2023poster

Large-scale neural networks possess considerable expressive power. They are well-suited for complex learning tasks in industrial applications. However, large-scale models pose significant challenges for training under the current Federated Learning (FL) paradigm. Existing approaches for efficient FL…

2021

HyDRA: Hypergradient Data Relevance Analysis for Interpreting Deep Neural Networks

AAAI 2021technical

The behaviors of deep neural networks (DNNs) are notoriously resistant to human interpretations. In this paper, we propose Hypergradient Data Relevance Analysis, or HyDRA, which interprets the predictions made by DNNs as effects of their training data. Existing approaches generally estimate data con…

2020

A novel and controllable cell-based microrobot in real vascular network for target tumor therapy

IROS 2020poster

Magnetic microrobots can be propelled precisely and wirelessly in vivo using magnetic field for targeted drug delivery and early detection. They are promising for clinical trials since magnetic fields are capable of penetrating most materials with minimal interaction, and are nearly harmless to huma…

Cited by 5SourceScholar
2020

Magnetized Cell-robot Propelled by Magnetic Field for Cancer Killing

IROS 2020poster

In this paper, we present a magnetized cell-robot using macrophages as templates, which can be controlled under a strong gradient magnetic field, to approach and kill cancer cells in both vitro and vivo environment. Firstly, we establish a magnetic control system using only four coils which can gene…

Cited by 3SourceScholar