Yu-Chiang Frank Wang
3 papers in the PaperMetrix corpus
Papers by this author
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FedBug: A Bottom-Up Gradual Unfreezing Framework for Federated Learning
2023 · arXiv (Cornell University)
Federated Learning (FL) offers a collaborative training framework, allowing multiple clients to contribute to a shared model without compromising data privacy. Due to the heterogeneous nature of local datasets, updated client models may overfit and …
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Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation
2023 · arXiv (Cornell University)
Federated learning (FL) emerges as a decentralized learning framework which trains models from multiple distributed clients without sharing their data to preserve privacy. Recently, large-scale pre-trained models (e.g., Vision Transformer) have shown a strong capability …
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Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning Data
2025
Recent end-to-end speech language models (SLMs) have expanded upon the capabilities of large language models (LLMs) by incorporating pre-trained speech models. However, these SLMs often undergo extensive speech instruction-tuning to bridge the gap between speech …