213 citations · 232 across the 15 of their papers we have counts for
16 papers
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…
Catalyst Papers in Artificial Intelligence Research: A Landscape on ICLR from 2017 to 2025
Fan Huang
A small number of methodological contributions, including word2vec, the Transformer, large-scale pre-training, and reinforcement learning from human feedback, have reshaped NLP and…
Simulating Hate Speech Cascades with Multi-LLM Agents: Empirical Grounding, Modeling Fidelity, and Intervention Strategies
Fan Huang
Faithful modeling of hateful content propagation on online platforms remains an open problem for moderation research. Classical cascade models that do not explicitly represent the…
Can LLMs Predict Academic Collaboration? Topology Heuristics vs. LLM-Based Link Prediction on Real Co-authorship Networks
Fan Huang, Munjung Kim
Can large language models (LLMs) predict which researchers will collaborate? We study this question through link prediction on real-world co-authorship networks from OpenAlex (9.96…
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…
Reasoning Topology Matters: Network-of-Thought for Complex Reasoning Tasks
Fan Huang
Existing prompting paradigms structure LLM reasoning in limited topologies: Chain-of-Thought (CoT) produces linear traces, while Tree-of-Thought (ToT) performs branching search. Ye…
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…
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…
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…
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…
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…
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…
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…
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…
Random Padding Data Augmentation
Nan Yang, Laicheng Zhong, Fan Huang +2
The convolutional neural network (CNN) learns the same object in different positions in images, which can improve the recognition accuracy of the model. An implication of this is t…
Chain of Explanation: New Prompting Method to Generate Higher Quality Natural Language Explanation for Implicit Hate Speech
Fan Huang, Haewoon Kwak, Jisun An
Recent studies have exploited advanced generative language models to generate Natural Language Explanations (NLE) for why a certain text could be hateful. We propose the Chain of E…