Author

Ya-Qi Yang

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#machine learning Preprint Sep 2026

World-as-Graph: Relational World Modeling Through Latent Space Graphs

The proposed World-As-Graph (WAG) is a graph-based object-centric world model that introduces relational inductive bias into JEPA-style predictive representation learning and could demonstrate the superior performance of the proposed WAG on both visual reasoning and robotic manipulation tasks.

Ya-Qi Yang, Shu-Wei Huang, Yu-Jin Huang et al. · 1 citation

Book Open access Jul 2026

Mitigating Bias in Large Language Model Based Question Answering through Causal Front Door Prompting

A Causal Front Door Prompting framework (CFDP) is proposed that reduces demographic influence by intervening on the chain of thought reasoning, which is treated as an observable mediator and consistently improves fairness metrics without sacrificing QA accuracy.

Ya-Qi Yang, Zi-Qi Xu, Jie Li et al. · Annual International ACM SIG... · 1 citation