5 papers
ASafe: Counterfactual Evidence-Aligned Adaptive Agent Collaboration for Safe and Effective Visual Question Answering
Quanxing Xu, Ling Zhou, Xian Zhong +4
Visual Question Answering (VQA) with Multimodal Large Language Models (MLLMs) requires not only producing safe and effective responses, but also grounding safety decisions in the m…
EGRL: Edge generation-guided relation-aware learning for RNA-protein interaction prediction
Danyu Li, Ling Zhou, Rubing Huang +3
RNA-Protein Interactions (RPIs) are critical for regulating cellular functions. While traditional wet-lab experiments for RPI detection are costly and time-consuming, Deep Learning…
STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks
Tianqing Zhang, Kairong Yu, Xian Zhong +3
Spiking Neural Networks (SNNs) have gained significant attention due to their biological plausibility and energy efficiency, making them promising alternatives to Artificial Neural…
PAD: Phase-Amplitude Decoupling Fusion for Multi-Modal Land Cover Classification
Huiling Zheng, Xian Zhong, Bin Liu +3
The fusion of Synthetic Aperture Radar (SAR) and RGB imagery for land cover classification remains challenging due to modality heterogeneity and underexploited spectral complementa…
Exploring Individual Factors in the Adoption of LLMs for Specific Software Engineering Purposes
Stefano Lambiase, Gemma Catolino, Fabio Palomba +2
Context: The advent of Large Language Models (LLMs) is transforming software development, significantly enhancing software engineering (SE) processes. Research has explored their r…