52 citations · 159 across the 24 of their papers we have counts for
25 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…
The Emergence of Causal Curiosity from Prior Causal Belief Networks
Zhuoyu Shi, Xintong Jiang, Bohan Jiang +1
Causal curiosity is foundational to human cognition. It is the desire to understand why events happen, what mechanisms underlie them, and how outcomes can be explained or anticipat…
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: Thwarting Unauthorized LLM Exploitation via RL-Driven Unlearnable Text
Chengshuai Zhao, Pingchuan Ma, Dawei Li +4
The rapid development of Large Language Models (LLMs) has led to significant advances across a wide range of language tasks, while simultaneously raising growing concerns about una…
Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence
Ujun Jeong, Saketh Vishnubhatla, Bohan Jiang +3
During disasters, extracting causal relations from social media can strengthen situational awareness by identifying factors linked to casualties, physical damage, infrastructure di…
CAMO: Causality-Guided Adversarial Multimodal Domain Generalization for Crisis Classification
Pingchuan Ma, Chengshuai Zhao, Bohan Jiang +5
Crisis classification in social media aims to extract actionable disaster-related information from multimodal posts, which is a crucial task for enhancing situational awareness and…
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…
An Interventional Approach to Real-Time Disaster Assessment via Causal Attribution
Saketh Vishnubhatla, Alimohammad Beigi, Rui Heng Foo +5
Traditional disaster analysis and modelling tools for assessing the severity of a disaster are predictive in nature. Based on the past observational data, these tools prescribe how…
Assessing On-the-Ground Disaster Impact Using Online Data Sources
Saketh Vishnubhatla, Ujun Jeong, Bohan Jiang +4
Assessing the impact of a disaster in terms of asset losses and human casualties is essential for preparing effective response plans. Traditional methods include offline assessment…
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 (…
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…
Preference Leakage: A Contamination Problem in LLM-as-a-judge
Dawei Li, Renliang Sun, Yue Huang +6
Large Language Models (LLMs) as judges and LLM-based data synthesis have emerged as two fundamental LLM-driven data annotation methods in model development. While their combination…
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…
Disinformation Detection: An Evolving Challenge in the Age of LLMs
Bohan Jiang, Zhen Tan, Ayushi Nirmal +1
The advent of generative Large Language Models (LLMs) such as ChatGPT has catalyzed transformative advancements across multiple domains. However, alongside these advancements, they…
SocioHub: An Interactive Tool for Cross-Platform Social Media Data Collection
Ayushi Nirmal, Bohan Jiang, Huan Liu
Social media is inherently about connecting and interacting with others. Different social media platforms have unique characteristics and user bases. Moreover, people use different…
CoVaxNet: An Online-Offline Data Repository for COVID-19 Vaccine Hesitancy Research
Bohan Jiang, Paras Sheth, Baoxin Li +1
Despite the astonishing success of COVID-19 vaccines against the virus, a substantial proportion of the population is still hesitant to be vaccinated, undermining governmental effo…
A Survey on Echo Chambers on Social Media: Description, Detection and Mitigation
Faisal Alatawi, Lu Cheng, Anique Tahir +4
Echo chambers on social media are a significant problem that can elicit a number of negative consequences, most recently affecting the response to COVID-19. Echo chambers promote c…
Mechanisms and Attributes of Echo Chambers in Social Media
Bohan Jiang, Mansooreh Karami, Lu Cheng +2
Echo chambers may exclude social media users from being exposed to other opinions, therefore, can cause rampant negative effects. Among abundant evidence are the 2016 and 2020 US p…