24 citations · 51 across the 15 of their papers we have counts for
3 papers · 1 filter
LLMRefine: Pinpointing and Refining Large Language Models via Fine-Grained Actionable Feedback
Wenda Xu, Daniel Deutsch, Mara Finkelstein +6
Recent large language models (LLM) are leveraging human feedback to improve their generation quality. However, human feedback is costly to obtain, especially during inference. In t…
Automatically Correcting Large Language Models: Surveying the landscape of diverse self-correction strategies
Liangming Pan, Michael Saxon, Wenda Xu +3
Large language models (LLMs) have demonstrated remarkable performance across a wide array of NLP tasks. However, their efficacy is undermined by undesired and inconsistent behavior…
INSTRUCTSCORE: Explainable Text Generation Evaluation with Finegrained Feedback
Wenda Xu, Danqing Wang, Liangming Pan +4
Automatically evaluating the quality of language generation is critical. Although recent learned metrics show high correlation with human judgement, these metrics can not explain t…