10 citations · 68 across the 39 of their papers we have counts for
41 papers
Probing Outcome-Level Resemblance and Mechanism-Level Alignment in LLM Risk Decisions: Evidence from the St. Petersburg Game
Chensong Huang, Changyu Chen, Chenwei Lin +3
LLMs can appear cautious in risk decision-making tasks, yet cautious-looking outputs do not necessarily indicate alignment with human decision-making mechanisms. We investigate thi…
Revising Context, Shifting Simulated Stance: Auditing LLM-Based Stance Simulation in Online Discussions
Xinnong Zhang, Wanting Shan, Hanjia Lyu +2
Large language models are increasingly used to simulate social media users and infer how individuals may respond to online discussions. However, it remains unclear whether these si…
Assessing Historical Structural Oppression Worldwide via Rule-Guided Prompting of Large Language Models
Sreejato Chatterjee, Linh Tran, Quoc Duy Nguyen +6
Traditional efforts to measure historical structural oppression struggle with cross-national validity due to the unique, locally specified histories of exclusion, colonization, and…
SocioVerse: A World Model for Social Simulation Powered by LLM Agents and A Pool of 10 Million Real-World Users
Xinnong Zhang, Jiayu Lin, Xinyi Mou +18
Social simulation is transforming traditional social science research by modeling human behavior through interactions between virtual individuals and their environments. With recen…
Can LLMs Simulate Social Media Engagement? A Study on Action-Guided Response Generation
Zhongyi Qiu, Hanjia Lyu, Wei Xiong +1
Social media enables dynamic user engagement with trending topics, and recent research has explored the potential of large language models (LLMs) for response generation. While som…
From Selection to Generation: A Survey of LLM-based Active Learning
Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie +31
Active Learning (AL) has been a powerful paradigm for improving model efficiency and performance by selecting the most informative data points for labeling and training. In recent…
Irony in Emojis: A Comparative Study of Human and LLM Interpretation
Yawen Zheng, Hanjia Lyu, Jiebo Luo
Emojis have become a universal language in online communication, often carrying nuanced and context-dependent meanings. Among these, irony poses a significant challenge for Large L…
Personalized Multimodal Large Language Models: A Survey
Junda Wu, Hanjia Lyu, Yu Xia +24
Multimodal Large Language Models (MLLMs) have become increasingly important due to their state-of-the-art performance and ability to integrate multiple data modalities, such as tex…
CRTRE: Causal Rule Generation with Target Trial Emulation Framework
Junda Wang, Weijian Li, Han Wang +5
Causal inference and model interpretability are gaining increasing attention, particularly in the biomedical domain. Despite recent advance, decorrelating features in nonlinear env…
ElectionSim: Massive Population Election Simulation Powered by Large Language Model Driven Agents
Xinnong Zhang, Jiayu Lin, Libo Sun +10
The massive population election simulation aims to model the preferences of specific groups in particular election scenarios. It has garnered significant attention for its potentia…
Semantics Preserving Emoji Recommendation with Large Language Models
Zhongyi Qiu, Kangyi Qiu, Hanjia Lyu +2
Emojis have become an integral part of digital communication, enriching text by conveying emotions, tone, and intent. Existing emoji recommendation methods are primarily evaluated…
Representation Bias in Political Sample Simulations with Large Language Models
Weihong Qi, Hanjia Lyu, Jiebo Luo
This study seeks to identify and quantify biases in simulating political samples with Large Language Models, specifically focusing on vote choice and public opinion. Using the GPT-…
INS-MMBench: A Comprehensive Benchmark for Evaluating LVLMs' Performance in Insurance
Chenwei Lin, Hanjia Lyu, Xian Xu +1
Large Vision-Language Models (LVLMs) and Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance in various general multimodal applications and have show…
Harnessing GPT-4V(ision) for Insurance: A Preliminary Exploration
Chenwei Lin, Hanjia Lyu, Jiebo Luo +1
The emergence of Large Multimodal Models (LMMs) marks a significant milestone in the development of artificial intelligence. Insurance, as a vast and complex discipline, involves a…
SoMeLVLM: A Large Vision Language Model for Social Media Processing
Xinnong Zhang, Haoyu Kuang, Xinyi Mou +6
The growth of social media, characterized by its multimodal nature, has led to the emergence of diverse phenomena and challenges, which calls for an effective approach to uniformly…
In the Eyes of the Bystander: Are the Stances on Different Conflicts Correlated?
Yiyao Tao, Hengyu Zhang, Babli Dey +3
Public opinion on international conflicts, such as the concurrent Russia-Ukraine and Israel-Palestine crises, often reflects a society's values, beliefs, and history. These simulta…
CoCoT: Contrastive Chain-of-Thought Prompting for Large Multimodal Models with Multiple Image Inputs
Daoan Zhang, Junming Yang, Hanjia Lyu +4
When exploring the development of Artificial General Intelligence (AGI), a critical task for these models involves interpreting and processing information from multiple image input…
Human vs. LMMs: Exploring the Discrepancy in Emoji Interpretation and Usage in Digital Communication
Hanjia Lyu, Weihong Qi, Zhongyu Wei +1
Leveraging Large Multimodal Models (LMMs) to simulate human behaviors when processing multimodal information, especially in the context of social media, has garnered immense intere…
GPT-4V(ision) as A Social Media Analysis Engine
Hanjia Lyu, Jinfa Huang, Daoan Zhang +6
Recent research has offered insights into the extraordinary capabilities of Large Multimodal Models (LMMs) in various general vision and language tasks. There is growing interest i…
Excitements and Concerns in the Post-ChatGPT Era: Deciphering Public Perception of AI through Social Media Analysis
Weihong Qi, Jinsheng Pan, Hanjia Lyu +1
As AI systems become increasingly prevalent in various aspects of daily life, gaining a comprehensive understanding of public perception towards these AI systems has become increas…
LLM-Rec: Personalized Recommendation via Prompting Large Language Models
Hanjia Lyu, Song Jiang, Hanqing Zeng +7
Text-based recommendation holds a wide range of practical applications due to its versatility, as textual descriptions can represent nearly any type of item. However, directly empl…
Dismantling Hate: Understanding Hate Speech Trends Against NBA Athletes
Edinam Kofi Klutse, Samuel Nuamah-Amoabeng, Hanjia Lyu +1
Social media has emerged as a popular platform for sports fans to express their opinions regarding athletes' performance. Fans consistently hold high expectations for athletes, ant…
Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
Jingyang Lin, Junyu Chen, Hanjia Lyu +6
Diagnosis of adverse neonatal outcomes is crucial for preterm survival since it enables doctors to provide timely treatment. Machine learning (ML) algorithms have been demonstrated…
Human Behavior in the Time of COVID-19: Learning from Big Data
Hanjia Lyu, Arsal Imtiaz, Yufei Zhao +1
Since the World Health Organization (WHO) characterized COVID-19 as a pandemic in March 2020, there have been over 600 million confirmed cases of COVID-19 and more than six million…