1 citations · 2 across the 5 of their papers we have counts for
5 papers
Integrating LLM-Derived Multi-Semantic Intent into Graph Model for Session-based Recommendation
Shuo Zhang, Xiao Li, Jiayi Wu +3
Session-based recommendation (SBR) is mainly based on anonymous user interaction sequences to recommend the items that the next user is most likely to click. Currently, the most po…
Structure-aware Fine-tuning for Code Pre-trained Models
Jiayi Wu, Renyu Zhu, Nuo Chen +3
Over the past few years, we have witnessed remarkable advancements in Code Pre-trained Models (CodePTMs). These models achieved excellent representation capabilities by designing s…
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…
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…
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…