output
20162026
most citedSwinVRNN: A Data-Driven Ensemble Forecasting Model via Learned Distribution Perturbation

65 citations

41 papers

cs.LG2026

Federated Learning Playground

Bryan Shan, Alysa Ziying Tan, Han Yu

We present Federated Learning Playground, an interactive browser-based platform inspired by and extends TensorFlow Playground that teaches core Federated Learning (FL) concepts. Us…

cs.CV2025★ 1 cited

Non-Contrast CT Esophageal Varices Grading through Clinical Prior-Enhanced Multi-Organ Analysis

Xiaoming Zhang, Chunli Li, Jiacheng Hao +9

Esophageal varices (EV) represent a critical complication of portal hypertension, affecting approximately 60% of cirrhosis patients with a significant bleeding risk of ~30%. While…

cs.CL2025★ 9 cited

ESGenius: Benchmarking LLMs on Environmental, Social, and Governance (ESG) and Sustainability Knowledge

Chaoyue He, Xin Zhou, Yi Wu +9

We introduce ESGenius, a comprehensive benchmark for evaluating and enhancing the proficiency of Large Language Models (LLMs) in Environmental, Social, and Governance (ESG) and sus…

cs.LG2025★ 9 cited

FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification

Tian Tian, Chunyan Miao, Hangwei Qian

Contrastive learning has emerged as a competent approach for unsupervised representation learning. However, the design of an optimal augmentation strategy, although crucial for con…

cs.LG2025★ 4 cited

A Survey of Graph Transformers: Architectures, Theories and Applications

Chaohao Yuan, Kangfei Zhao, Ercan Engin Kuruoglu +6

Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph neural networks (GNNs), such as over-sm…

eess.IV2024★ 3 cited

Generative Human Video Compression with Multi-granularity Temporal Trajectory Factorization

Shanzhi Yin, Bolin Chen, Shiqi Wang +1

In this paper, we propose a novel Multi-granularity Temporal Trajectory Factorization framework for generative human video compression, which holds great potential for bandwidth-co…