7 papers
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…