1 citations · 2 across the 7 of their papers we have counts for
7 papers
VLBM: Variational Latent Basis Modeling for OOD Robust Multivariate Time Series Forecasting
Xudong Zhang, Jierui Lei, Jiacheng Li +3
Out of distribution (OOD) events in multivariate time series forecasting are rare but often dominate real world risk, making average case forecasting insufficient for reliable depl…
From Supervision to Exploration: What Does Protein Language Model Learn During Reinforcement Learning?
Hanqun Cao, Hongrui Zhang, Junde Xu +12
Protein language models (PLMs) have advanced computational protein science through large-scale pretraining and scalable architectures. In parallel, reinforcement learning (RL) has…
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…
Towards a Multimodal Large Language Model with Pixel-Level Insight for Biomedicine
Xiaoshuang Huang, Lingdong Shen, Jia Liu +4
In recent years, Multimodal Large Language Models (MLLM) have achieved notable advancements, demonstrating the feasibility of developing an intelligent biomedical assistant. Howeve…
A Refer-and-Ground Multimodal Large Language Model for Biomedicine
Xiaoshuang Huang, Haifeng Huang, Lingdong Shen +4
With the rapid development of multimodal large language models (MLLMs), especially their capabilities in visual chat through refer and ground functionalities, their significance is…
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…