5+ day, 6+ hour ago   (424+ words) predictive model to address student dropout in higher education, using advanced artificial intelligence techniques,...

1+ week, 4+ day ago   (319+ words) Existing scientific text representation methods based on contrastive learning typically adopt a binary classification paradigm of positive and negative samples, which struggles to capture the complex, hierarchical semantic similarity relationships inherent in scientific texts. To address this, we propose SciRep,…...

1+ week, 6+ day ago   (486+ words) Federated learning relies on aggregation schemes that assume all participants train models with identical architectures and a common parameter initialization. While this enables parameter-averaging strategies such as Federated Averaging, it also imposes a strong inductive bias by constraining local models…...

5+ day, 4+ hour ago   (435+ words) Emergency-information analysts need to organize image-text reports into humanitarian categories before reports can be verified and prioritized. This study asks whether fine-grained evidence refinement can be added to an established classifier without replacing its decision path or greatly enlarging the…...

3+ hour, 46+ min ago   (361+ words) This research investigates the security of large language models (LLMs) with the aim of identifying key security and safety threats, control measures, and governance considerations that are relevant to their trustworthy adoption in the Extended Reality (XR) domain. To achieve…...

3+ week, 1+ day ago   (429+ words) Knowledge-Tracing (KT) models typically rely on ID-based representations, such as question IDs and skill IDs, which limit their generalizability to unseen questions (cold-question scenarios). In this study, we improve the generalization of cold-question scenarios by embedding a MathBERT-based semantic question…...

2+ week, 2+ day ago   (494+ words) Vision-based traffic accident anticipation is critical for active vehicle safety systems, yet existing architectures frequently conflate performance gains with heavy parameter scaling optimized from scratch on compact domains. Consequently, during real-time inference, these frameworks suffer from severe prediction volatility and…...

1+ week, 4+ day ago   (445+ words) Automated essay scoring models trained on imbalanced examination data often compress predictions toward the score mean, disproportionately harming low-proficiency responses. We investigate whether synthetic tail data can mitigate this failure in Chinese second-language writing assessment. Using 10,067 HSK writing samples, we…...

2+ week, 5+ day ago   (407+ words) Large-scale administrative hospital discharge data is a key resource for secondary health systems research, yet reuse is constrained by barriers of access, quality, interoperability, and semantic comparability. This paper presents and validates a reproducible, declarative, loss-aware harmonization framework for public…...

2+ week, 1+ day ago   (344+ words) High-resolution remote sensing understanding requires models to preserve small spatial evidence, account for acquisition-dependent appearance, and separate genuine geographic change from nuisance variation. We introduce GeoGATE, a geo-sensor-guided framework that combines typed acquisition conditioning, budget-constrained adaptive token acquisition, metadata-compatible evidence…...