4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.LG2024★ 1 cited
Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models
Lanning Wei, Jun Gao, Huan Zhao +1
Graph-structured data are the commonly used and have wide application scenarios in the real world. For these diverse applications, the vast variety of learning tasks, graph domains…
cs.CL2024★ 4 cited
EventRL: Enhancing Event Extraction with Outcome Supervision for Large Language Models
Jun Gao, Huan Zhao, Wei Wang +2
In this study, we present EventRL, a reinforcement learning approach developed to enhance event extraction for large language models (LLMs). EventRL utilizes outcome supervision wi…
cs.CL2023★ 2 cited
Benchmarking Large Language Models with Augmented Instructions for Fine-grained Information Extraction
Jun Gao, Huan Zhao, Yice Zhang +3
Information Extraction (IE) is an essential task in Natural Language Processing. Traditional methods have relied on coarse-grained extraction with simple instructions. However, wit…