69 citations · 72 across the 5 of their papers we have counts for
5 papers
Preference-Guided Refactored Tuning for Retrieval Augmented Code Generation
Xinyu Gao, Yun Xiong, Deze Wang +4
Retrieval-augmented code generation utilizes Large Language Models as the generator and significantly expands their code generation capabilities by providing relevant code, documen…
Towards Proactive Interactions for In-Vehicle Conversational Assistants Utilizing Large Language Models
Huifang Du, Xuejing Feng, Jun Ma +5
Research demonstrates that the proactivity of in-vehicle conversational assistants (IVCAs) can help to reduce distractions and enhance driving safety, better meeting users' cogniti…
KADEL: Knowledge-Aware Denoising Learning for Commit Message Generation
Wei Tao, Yucheng Zhou, Yanlin Wang +3
Commit messages are natural language descriptions of code changes, which are important for software evolution such as code understanding and maintenance. However, previous methods…
Plug-and-Play Feature Generation for Few-Shot Medical Image Classification
Qianyu Guo, Huifang Du, Xing Jia +4
Few-shot learning (FSL) presents immense potential in enhancing model generalization and practicality for medical image classification with limited training data; however, it still…
Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System
Yunfan Gao, Tao Sheng, Youlin Xiang +3
Large language models (LLMs) have demonstrated their significant potential to be applied for addressing various application tasks. However, traditional recommender systems continue…