Author

Chih-Yung Chang

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Jul 2026

DRIFT: Regime-Aware Self-Supervised Learning, Zero-Inflated Forecasting, and Inference Fusion for Metro OD Demand under Temporal Distribution Shift

Results indicate that jointly modeling regime consistency and sparsity is effective for long-horizon OD forecasting, and that the core representation and sparsity-aware designs alone, without the inference-time fusion, already surpass all baselines.

Hsiang-Chuan Chang, Tzu-Chia Huang, Chih-Yung Chang et al. · Journal of Internet Technolo... · 0 citations

Aug 2026

STaR: a soft-labeling and triplet-aware retriever for efficient retrieval-augmented QA

This study proposes STaR, a novel retriever fine-tuning framework that integrates BM25 similarity graph-based soft labeling with a triplet similarity learning strategy based on Sentence-BERT (SBERT), and introduces a triplet-aware SBERT training architecture that explicitly models relative semantic distances between qu...

Jiali Jiang, Chih-Yung Chang, Youxi Li et al. · Multimedia Systems · 0 citations