9 papers
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…
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…
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…
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…