52 citations · 159 across the 24 of their papers we have counts for
7 papers · 1 filter
In-Group Love, Out-Group Hate: A Framework to Measure Affective Polarization via Contentious Online Discussions
Buddhika Nettasinghe, Ashwin Rao, Bohan Jiang +2
Affective polarization, the emotional divide between ideological groups marked by in-group love and out-group hate, has intensified in the United States, driving contentious issues…
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…
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…
Can LLMs Improve Multimodal Fact-Checking by Asking Relevant Questions?
Alimohammad Beigi, Bohan Jiang, Dawei Li +5
Traditional fact-checking relies on humans to formulate relevant and targeted fact-checking questions (FCQs), search for evidence, and verify the factuality of claims. While Large…
Catching Chameleons: Detecting Evolving Disinformation Generated using Large Language Models
Bohan Jiang, Chengshuai Zhao, Zhen Tan +1
Despite recent advancements in detecting disinformation generated by large language models (LLMs), current efforts overlook the ever-evolving nature of this disinformation. In this…
Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media
Bohan Jiang, Lu Cheng, Zhen Tan +2
News media has been utilized as a political tool to stray from facts, presenting biased claims without evidence. Amid the COVID-19 pandemic, politically biased news (PBN) has signi…
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…