8 papers
Silicon Sampling via Cross-Survey Transfer
Chan-Tung Ku, Chan Hsu, Pei-Cing Huang +3
Silicon sampling-using large language models (LLMs) to simulate human survey respondents-has emerged as a promising approach for augmenting traditional survey research. However, mo…
ADVENT: LLM-Driven Automatic Predicate Invention for ILP
Tingting Yu, Pei-Cing Huang, Chan Hsu +2
Predicate invention (PI), the creation of new predicates to extend the hypothesis space, remains a critical bottleneck in Inductive Logic Programming (ILP). Existing methods rely o…
Latent Confidence Alignment for LLM Self-Assessment
Ting-Yu Chen, Tingting Yu, Pei-Cing Huang +3
Confidence calibration in large language models (LLMs) is commonly evaluated by comparing predicted confidence with observed accuracy. However, such approaches do not model item di…
ForEx: A Formal Verification Framework for Explainable Reasoning in Logical Fallacy Detection and Annotation
Pei-Cing Huang, Chienyu Liu, Chan Hsu +3
Current evaluations of Large Language Models (LLMs) on logical fallacy detection focus on predicted labels, but do not establish whether those labels are supported by the reasoning…
LLM-based Agents for Automated Confounder Discovery and Subgroup Analysis in Causal Inference
Po-Han Lee, Yu-Cheng Lin, Chan-Tung Ku +4
Estimating individualized treatment effects from observational data presents a persistent challenge due to unmeasured confounding and structural bias. Causal Machine Learning (caus…
Towards Simulating Social Influence Dynamics with LLM-based Multi-agents
Hsien-Tsung Lin, Pei-Cing Huang, Chan-Tung Ku +3
Recent advancements in Large Language Models offer promising capabilities to simulate complex human social interactions. We investigate whether LLM-based multi-agent simulations ca…