25 citations · 25 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Can Large Language Models be Trusted for Evaluation? Scalable Meta-Evaluation of LLMs as Evaluators via Agent Debate
Steffi Chern, Ethan Chern, Graham Neubig +1
Despite the utility of Large Language Models (LLMs) across a wide range of tasks and scenarios, developing a method for reliably evaluating LLMs across varied contexts continues to…
cs.CL2024
Combating Adversarial Attacks with Multi-Agent Debate
Steffi Chern, Zhen Fan, Andy Liu
While state-of-the-art language models have achieved impressive results, they remain susceptible to inference-time adversarial attacks, such as adversarial prompts generated by red…
cs.CL2023★ 25 cited
FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios
I-Chun Chern, Steffi Chern, Shiqi Chen +6
The emergence of generative pre-trained models has facilitated the synthesis of high-quality text, but it has also posed challenges in identifying factual errors in the generated t…