activity
20162026
most citedIs ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speech

213 citations · 383 across the 32 of their papers we have counts for

collaborators

34 papers

cs.RO2026

Instruction-Conditioned Motion Control for Robotic Arms: Language-to-Code Decomposition and Reinforcement Learning

Fan Huang, Dezhong Tong, Changyu Chen +2

Instruction-Conditioned Motion Control (ICMC) separates parameter specification, instruction generation, and code synthesis for language-driven robot control, making execution outc…

cs.MA2026

Behavior is Not Enough: A Mechanism-Based Evaluation of Social Norm Emergence in LLM Societies

Rasika Muralidharan, Haewoon Kwak, Jisun An

Social norms cannot be identified from behavior alone: the same cooperative equilibrium may reflect shared expectations, strategic incentives, or simple imitation. Yet in multi-age…

cs.CL2026

PluRule: A Benchmark for Moderating Pluralistic Communities on Social Media

Zoher Kachwala, Bao Tran Truong, Rasika Muralidharan +3

Social media are shifting towards pluralism -- community-governed platforms where groups define their own norms. What violates rules in one community may be perfectly acceptable in…

cs.AI2026

CogBias: Measuring and Mitigating Cognitive Bias in Large Language Models

Fan Huang, Songheng Zhang, Haewoon Kwak +1

Large Language Models (LLMs) are increasingly deployed in high-stakes decision-making contexts. While prior work has shown that LLMs exhibit cognitive biases behaviorally, whether…

cs.CL2026

SynSym: A Synthetic Data Generation Framework for Psychiatric Symptom Identification

Migyeong Kang, Jihyun Kim, Hyolim Jeon +6

Psychiatric symptom identification on social media aims to infer fine-grained mental health symptoms from user-generated posts, allowing a detailed understanding of users' mental s…

cs.CL2026

Understanding Moral Reasoning Trajectories in Large Language Models: Toward Probing-Based Explainability

Fan Huang, Haewoon Kwak, Jisun An

Large language models (LLMs) increasingly participate in morally sensitive decision-making, yet how they organize ethical frameworks across reasoning steps remains underexplored. W…

cs.SI2026

LLMs Can Infer Political Alignment from Online Conversations

Byunghwee Lee, Sangyeon Kim, Filippo Menczer +3

Due to the correlational structure in our traits such as identities, cultures, and political attitudes, seemingly innocuous preferences like following a band or using a specific sl…

cs.AI2026

XChoice: Explainable Evaluation of AI-Human Alignment in LLM-based Constrained Choice Decision Making

Weihong Qi, Fan Huang, Rasika Muralidharan +2

We present XChoice, an explainable framework for evaluating AI-human alignment in constrained decision making. Moving beyond outcome agreement such as accuracy and F1 score, XChoic…

cs.CL2026★ 1 cited

Vulnerability of LLMs' Stated Beliefs? LLMs Belief Resistance Check Through Strategic Persuasive Conversation Interventions

Fan Huang, Haewoon Kwak, Jisun An

Large Language Models (LLMs) are increasingly employed in various question-answering tasks. However, recent studies showcase that LLMs are susceptible to persuasion and could adopt…

cs.CL2025

What Helps Language Models Predict Human Beliefs: Demographics or Prior Stances?

Joseph Malone, Rachith Aiyappa, Byunghwee Lee +3

Beliefs shape how people reason, communicate, and behave. Rather than existing in isolation, they exhibit a rich correlational structure--some connected through logical dependencie…

cs.CL2025

Can Lessons From Human Teams Be Applied to Multi-Agent Systems? The Role of Structure, Diversity, and Interaction Dynamics

Rasika Muralidharan, Haewoon Kwak, Jisun An

Multi-Agent Systems (MAS) with Large Language Model (LLM)-powered agents are gaining attention, yet fewer studies explore their team dynamics. Inspired by human team science, we pr…

cs.CY2025

Gendered Cultural Discourse in Japan across the Prewar-Postwar Transition: Evidence from Historical Word Embeddings

Shintaro Sakai, Haewoon Kwak, Jisun An +1

We quantify the evolution of gender stereotypes in Japan from 1900 to 1998, covering the prewar-postwar transition, using a series of yearly word embeddings trained on historical t…

cs.CL2025

Cognitive Linguistic Identity Fusion Score (CLIFS): A Scalable Cognition-Informed Approach to Quantifying Identity Fusion from Text

Devin R. Wright, Jisun An, Yong-Yeol Ahn

Quantifying identity fusion -- the psychological merging of self with another entity or abstract target (e.g., a religious group, political party, ideology, value, brand, belief, e…

cs.CL2025

Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMs

Shintaro Sakai, Jisun An, Migyeong Kang +1

Prior clinical psychology research shows that Western individuals with depression tend to report psychological symptoms, while Eastern individuals report somatic ones. We test whet…

cs.CL2025

A Cross-Cultural Comparison of LLM-based Public Opinion Simulation: Evaluating Chinese and U.S. Models on Diverse Societies

Weihong Qi, Fan Huang, Jisun An +1

This study evaluates the ability of DeepSeek, an open-source large language model (LLM), to simulate public opinions in comparison to LLMs developed by major tech companies. By com…

cs.CL2024★ 3 cited

A semantic embedding space based on large language models for modelling human beliefs

Byunghwee Lee, Rachith Aiyappa, Yong-Yeol Ahn +2

Beliefs form the foundation of human cognition and decision-making, guiding our actions and social connections. A model encapsulating beliefs and their interrelationships is crucia…

cs.CL2024★ 1 cited

Rematch: Robust and Efficient Matching of Local Knowledge Graphs to Improve Structural and Semantic Similarity

Zoher Kachwala, Jisun An, Haewoon Kwak +1

Knowledge graphs play a pivotal role in various applications, such as question-answering and fact-checking. Abstract Meaning Representation (AMR) represents text as knowledge graph…

cs.CL2024

ChatGPT Rates Natural Language Explanation Quality Like Humans: But on Which Scales?

Fan Huang, Haewoon Kwak, Kunwoo Park +1

As AI becomes more integral in our lives, the need for transparency and responsibility grows. While natural language explanations (NLEs) are vital for clarifying the reasoning behi…

cs.CL2024★ 2 cited

Benchmarking zero-shot stance detection with FlanT5-XXL: Insights from training data, prompting, and decoding strategies into its near-SoTA performance

Rachith Aiyappa, Shruthi Senthilmani, Jisun An +2

We investigate the performance of LLM-based zero-shot stance detection on tweets. Using FlanT5-XXL, an instruction-tuned open-source LLM, with the SemEval 2016 Tasks 6A, 6B, and P-…

cs.CL2024

ToBlend: Token-Level Blending With an Ensemble of LLMs to Attack AI-Generated Text Detection

Fan Huang, Haewoon Kwak, Jisun An

The robustness of AI-content detection models against sophisticated adversarial strategies, such as paraphrasing or word switching, is a rising concern in natural language generati…

cs.SI2023★ 4 cited

Public Perception of Generative AI on Twitter: An Empirical Study Based on Occupation and Usage

Kunihiro Miyazaki, Taichi Murayama, Takayuki Uchiba +2

The emergence of generative AI has sparked substantial discussions, with the potential to have profound impacts on society in all aspects. As emerging technologies continue to adva…

cs.CY2023★ 1 cited

YouNICon: YouTube's CommuNIty of Conspiracy Videos

Shaoyi Liaw, Fan Huang, Fabricio Benevenuto +2

Conspiracy theories are widely propagated on social media. Among various social media services, YouTube is one of the most influential sources of news and entertainment. This paper…

cs.SI2023★ 5 cited

Wearing Masks Implies Refuting Trump?: Towards Target-specific User Stance Prediction across Events in COVID-19 and US Election 2020

Hong Zhang, Haewoon Kwak, Wei Gao +1

People who share similar opinions towards controversial topics could form an echo chamber and may share similar political views toward other topics as well. The existence of such c…

cs.CL2023★ 213 cited

Is ChatGPT better than Human Annotators? Potential and Limitations of ChatGPT in Explaining Implicit Hate Speech

Fan Huang, Haewoon Kwak, Jisun An

Recent studies have alarmed that many online hate speeches are implicit. With its subtle nature, the explainability of the detection of such hateful speech has been a challenging p…