collaborators

8 papers

cs.CV2026

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…

cs.LG2026

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…

cs.CV2026

MetaRA: Metamorphic Robustness Assessment for Multimodal Large Language Model-based Visual Question Answering Systems

Quanxing Xu, Yuhao Tian, Ling Zhou +4

Visual Question Answering (VQA), as the representative multimodal task, serves as a key benchmark for evaluating the reasoning capabilities of Multimodal Large Language Models (MLL…

cs.CV2026

Enhancing Visual Question Answering with Multimodal LLMs via Chain-of-Question Guided Retrieval-Augmented Generation

Quanxing Xu, Ling Zhou, Xian Zhong +3

With advances in multimodal research and deep learning, Multimodal Large Language Models (MLLMs) have emerged as a powerful paradigm for a wide range of multimodal tasks. As a core…

cs.CL2026

PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention

Maoheng Li, Ling Zhou, Xiaohua Huang +3

Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial attention in multimodal under…

cs.LG2026

Short-term electricity load forecasting with multi-frequency reconstruction diffusion

Qi Dong, Rubing Huang, Ling Zhou +3

Diffusion models have emerged as a powerful method in various applications. However, their application to Short-Term Electricity Load Forecasting (STELF) -- a typical scenario in e…

cs.CV2025

OAD-Promoter: Enhancing Zero-shot VQA using Large Language Models with Object Attribute Description

Quanxing Xu, Ling Zhou, Feifei Zhang +2

Large Language Models (LLMs) have become a crucial tool in Visual Question Answering (VQA) for handling knowledge-intensive questions in few-shot or zero-shot scenarios. However, t…

cs.SE2025

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…