1 citations · 1 across the 12 of their papers we have counts for
13 papers
Cognition on Graph: Navigating Massive Knowledge Space via Cognitive Cycles and Bidirectional Graph-Text Synergy
Gengxian Zhou, Jian Xu, Zichen Tang +3
Retrieval-Augmented Generation (RAG) has empowered Large Language Models (LLMs) to tackle knowledge-intensive tasks. However, navigating global, heterogeneous knowledge bases (larg…
CatalyticMLLM: A Graph-Text Multimodal Large Language Model for Catalytic Materials
Yanjie Li, Jian Xu, Xu-Yao Zhang +4
Property prediction and inverse structural design of catalytic materials are typically modeled as two independent tasks: the former predicts target properties from given structures…
PA-Net: Precipitation-Adaptive Mixture-of-Experts for Long-Tail Rainfall Nowcasting
Xinyu Xiao, Sen Lei, Eryun Liu +5
Precipitation nowcasting is vital for flood warning, agricultural management, and emergency response, yet two bottlenecks persist: the prohibitive cost of modeling million-scale sp…
MeTok: An Efficient Meteorological Tokenization with Hyper-Aligned Group Learning for Precipitation Nowcasting
Qizhao Jin, Xianhuang Xu, Yong Cao +2
Recently, Transformer-based architectures have advanced meteorological prediction. However, this position-centric tokenizer conflicts with the core principle of meteorological syst…
SeaVIS: Sound-Enhanced Association for Online Audio-Visual Instance Segmentation
Yingjian Zhu, Ying Wang, Yuyang Hong +5
Recently, an audio-visual instance segmentation (AVIS) task has been introduced, aiming to identify, segment and track individual sounding instances in videos. However, prevailing…
HVR-Met: A Hypothesis-Verification-Replanning Agentic System for Extreme Weather Diagnosis
Shuo Tang, Jiadong Zhang, Gengxian Zhou +11
While deep learning-based weather forecasting paradigms have made significant strides, addressing extreme weather diagnostics remains a formidable challenge. This gap exists primar…
InfEngine: A Self-Verifying and Self-Optimizing Intelligent Engine for Infrared Radiation Computing
Kun Ding, Jian Xu, Ying Wang +2
Infrared radiation computing underpins advances in climate science, remote sensing and spectroscopy but remains constrained by manual workflows. We introduce InfEngine, an autonomo…
Beyond Next-Token Alignment: Distilling Multimodal Large Language Models via Token Interactions
Lin Chen, Xiaoke Zhao, Kun Ding +9
Multimodal Large Language Models (MLLMs) demonstrate impressive cross-modal capabilities, yet their substantial size poses significant deployment challenges. Knowledge distillation…
DSFC-Net: A Dual-Encoder Spatial and Frequency Co-Awareness Network for Rural Road Extraction
Zhengbo Zhang, Yihe Tian, Wanke Xia +6
Accurate extraction of rural roads from high-resolution remote sensing imagery is essential for infrastructure planning and sustainable development. However, this task presents uni…
EvoVLMA: Evolutionary Vision-Language Model Adaptation
Kun Ding, Ying Wang, Shiming Xiang
Pre-trained Vision-Language Models (VLMs) have been exploited in various Computer Vision tasks (e.g., few-shot recognition) via model adaptation, such as prompt tuning and adapters…
MeteorPred: A Meteorological Multimodal Large Model and Dataset for Severe Weather Event Prediction
Shuo Tang, Jian Xu, Jiadong Zhang +5
Timely and accurate forecasts of severe weather events are essential for early warning and for constraining downstream analysis and decision-making. Since severe weather events pre…
Rethinking Comprehensive Benchmark for Chart Understanding: A Perspective from Scientific Literature
Lingdong Shen, Qigqi, Kun Ding +2
Scientific Literature charts often contain complex visual elements, including multi-plot figures, flowcharts, structural diagrams and etc. Evaluating multimodal models using these…
SegICL: A Multimodal In-context Learning Framework for Enhanced Segmentation in Medical Imaging
Lingdong Shen, Fangxin Shang, Xiaoshuang Huang +3
In the field of medical image segmentation, tackling Out-of-Distribution (OOD) segmentation tasks in a cost-effective manner remains a significant challenge. Universal segmentation…