12 citations · 24 across the 17 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…
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…
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: Safeguarding Data from Unauthorized LLM Fine-Tuning via RL-Driven Unlearnable Examples
Chengshuai Zhao, Pingchuan Ma, Dawei Li +4
The development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concerns about unauthori…
Multimodal Large Language Models as Synthetic Participants in Video-Based Studies: An Evaluation
Prabal Shrestha, Bohan Jiang, Haoning Xue +2
Multimodal large language models (MLLMs) have shown strong performance on objective tasks such as video understanding and reasoning. However, it remains unclear whether they can ap…