Hidetsune at SemEval-2026 Task 10: A Systematic Exploration of Training and Inference Strategies for Detecting Conspiracy Beliefs
Year: 2026
Type: conference-paper
Abstract: This paper describes a system developed for SemEval-2026 Task 10 Subtask 2, which focuses on identifying conspiracy beliefs expressed in Reddit comments.The study begins with a comparative analysis of language models fine-tuned on the task data.In addition to finetuning, multiple auxiliary techniques were examined, including instruction-based prompting, data augmentation via back-translation, and a loss function designed to address label imbalance.In the final stage, the inference behavior was further examined by varying the decision threshold applied to the softmax output probabilities.The results highlight how choices made during model selection, training, and inference collectively affect performance, offering empirical insights into the challenges of conspiracy belief detection in social media contexts.
Author: Hidetsune Takahashi
Institution: Waseda University
Language: English
Subfield: Sociology and Political Science
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7166832552