52 citations · 159 across the 24 of their papers we have counts for
5 papers · 1 filter
What Social Media Teaches Us About Accumulative AI Risks
Dawei Li, Bohan Jiang, Huan Liu
Prominent AI safety discussions emphasize existential threats and catastrophic events, such as AI-enabled nuclear conflict or engineered biological outbreaks. This position paper a…
The Emergence of Causal Curiosity from Prior Causal Belief Networks
Zhuoyu Shi, Xintong Jiang, Bohan Jiang +1
Causal curiosity is foundational to human cognition. It is the desire to understand why events happen, what mechanisms underlie them, and how outcomes can be explained or anticipat…
Measuring and Detecting Harmful AI Sycophancy
Bohan Jiang, Dawei Li, Yasin Silva +1
Sycophantic responses are becoming pervasive in large language models (LLMs), and prior work has pointed out that some of them could be harmful. This paper focuses on one harmful s…
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…
Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence
Ujun Jeong, Saketh Vishnubhatla, Bohan Jiang +3
During disasters, extracting causal relations from social media can strengthen situational awareness by identifying factors linked to casualties, physical damage, infrastructure di…