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cs.LG2023★ 1 cited
Federated Learning via Consensus Mechanism on Heterogeneous Data: A New Perspective on Convergence
Shu Zheng, Tiandi Ye, Xiang Li +1
Federated learning (FL) on heterogeneous data (non-IID data) has recently received great attention. Most existing methods focus on studying the convergence guarantees for the globa…
cs.CL2023★ 1 cited
DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models
Chengcheng Han, Xiaowei Du, Che Zhang +4
Chain-of-Thought (CoT) prompting has proven to be effective in enhancing the reasoning capabilities of Large Language Models (LLMs) with at least 100 billion parameters. However, i…
cs.LG2023
Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding
Jianing Wang, Qiushi Sun, Nuo Chen +4
The recent success of large pre-trained language models (PLMs) heavily hinges on massive labeled data, which typically produces inferior performance in low-resource scenarios. To r…