40 citations · 40 across the 10 of their papers we have counts for
12 papers
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…
ToolPRMBench: Evaluating and Advancing Process Reward Models for Tool-using Agents
Dawei Li, Yuguang Yao, Zhen Tan +2
Reward-guided search methods have demonstrated strong potential in enhancing tool-using agents by effectively guiding sampling and exploration over complex action spaces. As a core…
From Moderation to Mediation: Can LLMs Serve as Mediators in Online Flame Wars?
Dawei Li, Abdullah Alnaibari, Arslan Bisharat +4
The rapid advancement of large language models (LLMs) has opened new possibilities for AI for good applications. As LLMs increasingly mediate online communication, their potential…
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…
Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era
Dawei Li, Yue Huang, Ming Li +3
Generative models such as Large Language Models, Diffusion Models, and generative adversarial networks have recently revolutionized the creation of synthetic data, offering scalabl…
Building Safer Sites: A Large-Scale Multi-Level Dataset for Construction Safety Research
Zhenhui Ou, Dawei Li, Zhen Tan +3
Construction safety research is a critical field in civil engineering, aiming to mitigate risks and prevent injuries through the analysis of site conditions and human factors. Howe…
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 (…
LLMs as World Models: Data-Driven and Human-Centered Pre-Event Simulation for Disaster Impact Assessment
Lingyao Li, Dawei Li, Zhenhui Ou +5
Efficient simulation is essential for enhancing proactive preparedness for sudden-onset disasters such as earthquakes. Recent advancements in large language models (LLMs) as world…
Beyond Accuracy: The Role of Calibration in Self-Improving Large Language Models
Liangjie Huang, Dawei Li, Huan Liu +1
Large Language Models (LLMs) have demonstrated remarkable self-improvement capabilities, whereby models iteratively revise their outputs through self-generated feedback. While this…
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…
Large Language Models for Data Annotation and Synthesis: A Survey
Zhen Tan, Dawei Li, Song Wang +7
Data annotation and synthesis generally refers to the labeling or generating of raw data with relevant information, which could be used for improving the efficacy of machine learni…