Foundation models for weather and climate data understanding: A comprehensive survey

S Chen, G Long, J Jiang, D Liu, C Zhang - ar** new realities: Ground truth image creation with pix2pix image-to-image translation
Z Li, B Guan, Y Wei, Y Zhou, J Zhang, J Xu - arxiv preprint arxiv …, 2024 - arxiv.org
Generative Adversarial Networks (GANs) have significantly advanced image processing,
with Pix2Pix being a notable framework for image-to-image translation. This paper explores …

Blockchain for large language model security and safety: A holistic survey

C Geren, A Board, GG Dagher, T Andersen… - ACM SIGKDD …, 2025 - dl.acm.org
With the growing development and deployment of large language models (LLMs) in both
industrial and academic fields, their security and safety concerns have become increasingly …

Unlocking the power of lstm for long term time series forecasting

Y Kong, Z Wang, Y Nie, T Zhou, S Zohren… - arxiv preprint arxiv …, 2024 - arxiv.org
Traditional recurrent neural network architectures, such as long short-term memory neural
networks (LSTM), have historically held a prominent role in time series forecasting (TSF) …

Cross-and Context-Aware Attention Based Spatial-Temporal Graph Convolutional Networks for Human Mobility Prediction

Z Mo, H **ang, X Di - ACM Transactions on Spatial Algorithms and …, 2024 - dl.acm.org
The COVID-19 pandemic has dramatically transformed human mobility patterns. Therefore,
human mobility prediction for the “new normal” is crucial to infrastructure redesign …

Hydro-informer: A deep learning model for accurate water level and flood predictions

W Almikaeel, A Šoltész, L Čubanová, D Baroková - Natural Hazards, 2024 - Springer
This study aims to develop an advanced deep learning model, Hydro-Informer, for accurate
water level and flood predictions, emphasizing extreme event forecasting. Utilizing a …

Towards Robust Vision Transformer via Masked Adaptive Ensemble

F Lin, J Lou, X Yuan, NF Tzeng - arxiv preprint arxiv:2407.15385, 2024 - arxiv.org
Adversarial training (AT) can help improve the robustness of Vision Transformers (ViT)
against adversarial attacks by intentionally injecting adversarial examples into the training …