14 citations · 36 across the 9 of their papers we have counts for
6 papers · 1 filter
Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning
Yue Yu, Jiaming Shen, Tianqi Liu +5
Large language models (LLMs) have shown remarkable capabilities in various natural language understanding tasks. With only a few demonstration examples, these LLMs can quickly adap…
Local Boosting for Weakly-Supervised Learning
Rongzhi Zhang, Yue Yu, Jiaming Shen +2
Boosting is a commonly used technique to enhance the performance of a set of base models by combining them into a strong ensemble model. Though widely adopted, boosting is typicall…
ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval
Yue Yu, Yuchen Zhuang, Rongzhi Zhang +3
With the development of large language models (LLMs), zero-shot learning has attracted much attention for various NLP tasks. Different from prior works that generate training data…
Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation
Rongzhi Zhang, Jiaming Shen, Tianqi Liu +4
Knowledge distillation is a popular technique to transfer knowledge from large teacher models to a small student model. Typically, the student learns to imitate the teacher by mini…
HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting
Jiaying Lu, Jiaming Shen, Bo Xiong +3
Medical decision-making processes can be enhanced by comprehensive biomedical knowledge bases, which require fusing knowledge graphs constructed from different sources via a unifor…
"Why is this misleading?": Detecting News Headline Hallucinations with Explanations
Jiaming Shen, Jialu Liu, Dan Finnie +3
Automatic headline generation enables users to comprehend ongoing news events promptly and has recently become an important task in web mining and natural language processing. With…