Integrating Multivariate Adaptive Regression Splines into Small Area Estimation for Nonlinear Poverty Modeling in Java Island
研究针对小区域估计中的非线性贫困问题,提出将多元自适应回归样条(MARS)与小区域估计框架结合的方法,以提高估计准确性。
研究针对小区域估计中的非线性贫困问题,提出将多元自适应回归样条(MARS)与小区域估计框架结合的方法,以提高估计准确性。
研究通过生产系统追踪评估五种Lazy Promotion策略,提出两种新方法D-FR和AGE以减少LRU中的不必要提升,同时保持或降低缺失率。
研究通过创建TutorTrace数据集和行为分类方法,利用IDE数据实时分析学习者的行为状态,以提高AI辅助编程教育的适应性。
This study addresses the challenge of visual geolocation in ASEAN countries, where highly similar urban landscapes hinder accurate and interpretable localization. To tackle this issue, the authors propose the first explainable, nation-level image geolocation framework covering all eleven ASEAN nations. The approach integrates CLIP zero-shot classification with LightGBM and MLP classifiers, and introduces a novel multi-dimensional interpretability pipeline combining CLIP attention rollout, YOLOv8 object detection, and Energy-Based Perturbation Games (EBPG) to uncover the key visual cues driving predictions. Experimental results demonstrate that the MLP model achieves 85.91% accuracy and F1 score on the test set while providing object-level fine-grained interpretability, revealing a notable discrepancy between frequently detected objects and regions receiving high attention weights.
This study addresses the limitations of traditional Ulos textile patterns—restricted variety and time-intensive design—which hinder the balance between cultural preservation and contemporary innovation. For the first time, the authors apply fine-tuned latent diffusion models to generate authentic Batak Ulos motifs from Indonesia, optimizing Protogen v3.4 and Stable Diffusion v1.4 on a high-quality dataset. Experimental results demonstrate that Protogen v3.4 substantially outperforms Stable Diffusion v1.4, achieving approximately a 10.5-fold reduction in FID and a two-fold increase in Inception Score. A guidance scale between 5 and 9 emerges as optimal, effectively balancing cultural fidelity with pattern diversity. This work not only enables creative regeneration while preserving cultural symbolism but also systematically elucidates how generation parameters influence the trade-off between fidelity and diversity.
研究针对小区域估计中的非线性贫困问题,提出将多元自适应回归样条(MARS)与小区域估计框架结合的方法,以提高估计准确性。
研究通过生产系统追踪评估五种Lazy Promotion策略,提出两种新方法D-FR和AGE以减少LRU中的不必要提升,同时保持或降低缺失率。
研究通过创建TutorTrace数据集和行为分类方法,利用IDE数据实时分析学习者的行为状态,以提高AI辅助编程教育的适应性。
This study addresses the challenge of visual geolocation in ASEAN countries, where highly similar urban landscapes hinder accurate and interpretable localization. To tackle this issue, the authors propose the first explainable, nation-level image geolocation framework covering all eleven ASEAN nations. The approach integrates CLIP zero-shot classification with LightGBM and MLP classifiers, and introduces a novel multi-dimensional interpretability pipeline combining CLIP attention rollout, YOLOv8 object detection, and Energy-Based Perturbation Games (EBPG) to uncover the key visual cues driving predictions. Experimental results demonstrate that the MLP model achieves 85.91% accuracy and F1 score on the test set while providing object-level fine-grained interpretability, revealing a notable discrepancy between frequently detected objects and regions receiving high attention weights.
This study addresses the limitations of traditional Ulos textile patterns—restricted variety and time-intensive design—which hinder the balance between cultural preservation and contemporary innovation. For the first time, the authors apply fine-tuned latent diffusion models to generate authentic Batak Ulos motifs from Indonesia, optimizing Protogen v3.4 and Stable Diffusion v1.4 on a high-quality dataset. Experimental results demonstrate that Protogen v3.4 substantially outperforms Stable Diffusion v1.4, achieving approximately a 10.5-fold reduction in FID and a two-fold increase in Inception Score. A guidance scale between 5 and 9 emerges as optimal, effectively balancing cultural fidelity with pattern diversity. This work not only enables creative regeneration while preserving cultural symbolism but also systematically elucidates how generation parameters influence the trade-off between fidelity and diversity.