Author

Jun-Cen Guo

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Preprint Oct 2026

DISCERN: Identifiable Disease Evidence for Generalizable Medical Multimodal Learning

Clinical multimodal models can learn enrollment shortcuts shared across modalities and fail on new cohorts. We model these data through a latent structural causal model: disease state and background factors generate physiology through shared mechanisms, while cohorts differ in selection and measurement. Holding acquisi...

Xiao-Guang Zhu, Peng-Yi Jiang, Jun-Cen Guo et al. · 0 citations

2026

Spatial–Temporal Decoupled Invertible Neural Networks for Skeleton-Based Video Anomaly Detection

Skeleton-based video anomaly detection has gained significant attention in security and forensics applications due to its privacy-preserving properties that abstract human motion without capturing identifiable biometric information. However, existing methods typically process spatial pose configurations and temporal mo...

Yang Liu, Lei Zhang, Jun-Cen Guo et al. · IEEE Transactions on Informa... · 0 citations

#natural language process... Preprint Sep 2026

Marginal Response Surface Elicitation for Zero-Label Tabular Learning

Tabular learning uses structured data to predict target outcomes. Traditionally, this process has relied on labeled data. However, large language models (LLMs) can be used to elicit domain priors based on the task description and feature semantics, thereby enabling predictions without labeled data. We propose Marginal...

Liang-Yu Teng, Yi-Chen Ding, Jing Liu et al. · 0 citations

#machine learning Preprint Sep 2026

Which Models Work Well Together? Measuring Heterogeneity for LLM Team Selection

The performance ceiling of an LLM team is constrained not only by individual model capabilities, but also by inter-member error resonance and predictive differences. Although heterogeneous teaming is often observed to be effective in practice, existing approaches lack complementarity metrics that are computable, interp...

Liang-Yu Teng, Heng-Song Liu, Jun-Cen Guo et al. · 0 citations

Aug 2026

GAF-Det: gated adaptive fusion detector for lightweight real-time object detection

Gated Adaptive Fusion Detector (GAF-Det), a single-stage detector whose neck replaces fixed-weight concatenation with a Lightweight Gated Feature Fusion (LGFF) module that dynamically computes per-channel fusion weights conditioned on both the semantic and spatial streams, demonstrating that input-adaptive feature fusi...

Xuxu Chu, Wenyang Fan, Yuanyuan Meng et al. · Journal of Real-Time Image P... · 0 citations

Jul 2026

CRISP: Pre-LLM Yet Text-Driven Visual Token Pruning for Efficient LVLM Inference

CRISP is proposed, a pre-LLM yet text-driven visual token pruning framework that preserves both instruction-relevant evidence and essential scene context that serves as a practical solution for efficient LVLM inference, especially in resource-constrained scenarios.

Xu Li, Yi Zheng, Mengyang Zhao et al. · arXiv.org · 1 citation