3 papers
cs.CL2024
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 (…
cs.CL2024
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 (…
cs.CL2024
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User Simulator
Chuyi Kong, Yaxin Fan, Xiang Wan +2
The unparalleled performance of closed-sourced ChatGPT has sparked efforts towards its democratization, with notable strides made by leveraging real user and ChatGPT dialogues, as…