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…
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…
Who's Your Judge? On the Detectability of LLM-Generated Judgments
Dawei Li, Zhen Tan, Chengshuai Zhao +6
Large Language Model (LLM)-based judgments leverage powerful LLMs to efficiently evaluate candidate content and provide judgment scores. However, the inherent biases and vulnerabil…
Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens
Chengshuai Zhao, Zhen Tan, Pingchuan Ma +5
Chain-of-Thought (CoT) prompting has been shown to be effective in eliciting structured reasoning (i.e., CoT reasoning) from large language models (LLMs). Regardless of its popular…
From Generation to Judgment: Opportunities and Challenges of LLM-as-a-judge
Dawei Li, Bohan Jiang, Liangjie Huang +10
Assessment and evaluation have long been critical challenges in artificial intelligence (AI) and natural language processing (NLP). Traditional methods, usually matching-based or s…