12 citations · 24 across the 17 of their papers we have counts for
6 papers · 1 filter
Adaptive Triggering for Bias Correction in LLM Reasoning
Nayoung Kim, Mickey Mancenido, Huan Liu
Chain-of-thought prompting can expose and amplify demographic stereotypes within an LLM's intermediate reasoning and create a failure mode that final-answer debiasing alone cannot…
TextCloak: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
Chengshuai Zhao, Pingchuan Ma, Dawei Li +4
The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concerns about una…
Are Today's LLMs Ready to Explain Well-Being Concepts?
Bohan Jiang, Dawei Li, Zhen Tan +2
Well-being encompasses mental, physical, and social dimensions essential to personal growth and informed life decisions. As individuals increasingly consult Large Language Models (…
Assessing the Impact of Conspiracy Theories Using Large Language Models
Bohan Jiang, Dawei Li, Zhen Tan +5
Measuring the relative impact of CTs is important for prioritizing responses and allocating resources effectively, especially during crises. However, assessing the actual impact of…
Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
Alimohammad Beigi, Bohan Jiang, Dawei Li +5
Traditional fact-checking relies on humans to formulate relevant and targeted fact-checking questions (FCQs), search for evidence, and verify the factuality of claims. While Large…
Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models
Bohan Jiang, Chengshuai Zhao, Zhen Tan +1
Despite recent advancements in detecting disinformation generated by large language models (LLMs), current efforts overlook the ever-evolving nature of this disinformation. In this…