51 citations · 67 across the 4 of their papers we have counts for
4 papers
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
An Empirical Study on Information Extraction using Large Language Models
Ridong Han, Chaohao Yang, Tao Peng +4
Human-like large language models (LLMs), especially the most powerful and popular ones in OpenAI's GPT family, have proven to be very helpful for many natural language processing (…
Document-level Relation Extraction with Relation Correlations
Ridong Han, Tao Peng, Benyou Wang +2
Document-level relation extraction faces two overlooked challenges: long-tail problem and multi-label problem. Previous work focuses mainly on obtaining better contextual represent…
Distantly Supervised Relation Extraction via Recursive Hierarchy-Interactive Attention and Entity-Order Perception
Ridong Han, Tao Peng, Jiayu Han +2
Wrong-labeling problem and long-tail relations severely affect the performance of distantly supervised relation extraction task. Many studies mitigate the effect of wrong-labeling…