7 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.CL2024
Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation
Tu Vu, Kalpesh Krishna, Salaheddin Alzubi +3
As large language models (LLMs) advance, it becomes more challenging to reliably evaluate their output due to the high costs of human evaluation. To make progress towards better LL…
cs.CL2023★ 7 cited
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation
Tu Vu, Mohit Iyyer, Xuezhi Wang +8
Most large language models (LLMs) are trained once and never updated; thus, they lack the ability to dynamically adapt to our ever-changing world. In this work, we perform a detail…