22 citations · 22 across the 7 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.SE2023
INTERVENOR: Prompting the Coding Ability of Large Language Models with the Interactive Chain of Repair
Hanbin Wang, Zhenghao Liu, Shuo Wang +4
This paper introduces INTERVENOR (INTERactiVE chaiN Of Repair), a system designed to emulate the interactive code repair processes observed in humans, encompassing both code diagno…
cs.CL2023★ 22 cited
UltraFeedback: Boosting Language Models with Scaled AI Feedback
Ganqu Cui, Lifan Yuan, Ning Ding +9
Learning from human feedback has become a pivot technique in aligning large language models (LLMs) with human preferences. However, acquiring vast and premium human feedback is bot…