activity
20172025
most citedLow-complexity Resource Allocation for Uplink RSMA in Future 6G Wireless Networks

28 citations · 31 across the 11 of their papers we have counts for

collaborators

11 papers

cs.ET2025

Cognitive-Radio Functionality: A Novel Configuration for STAR-RIS assisted RSMA Networks

Saeed Ibrahim, Yue Xiao, Dimitrios Tyrovolas +5

Cognitive radio rate-splitting multiple access (CR-RSMA) has emerged as a promising multiple access framework that can efficiently manage interference and adapt dynamically to hete…

physics.comp-ph2025

RT-APNN for Solving Gray Radiative Transfer Equations

Xizhe Xie, Wengu Chen, Zheng Ma +1

The Gray Radiative Transfer Equations (GRTEs) are high-dimensional, multiscale problems that pose significant computational challenges for traditional numerical methods. Current de…

math.NA2024

Capturing Shock Waves by Relaxation Neural Networks

Nan Zhou, Zheng Ma

In this paper, we put forward a neural network framework to solve the nonlinear hyperbolic systems. This framework, named relaxation neural networks(RelaxNN), is a simple and scala…

cs.MM2024

Probing Commonsense Reasoning Capability of Text-to-Image Generative Models via Non-visual Description

Mianzhi Pan, Jianfei Li, Mingyue Yu +4

Commonsense reasoning, the ability to make logical assumptions about daily scenes, is one core intelligence of human beings. In this work, we present a novel task and dataset for e…

math.NA20231 cited

Asymptotic-preserving neural networks for multiscale Vlasov-Poisson-Fokker-Planck system in the high-field regime

Shi Jin, Zheng Ma, Tian-ai Zhang

The Vlasov-Poisson-Fokker-Planck (VPFP) system is a fundamental model in plasma physics that describes the Brownian motion of a large ensemble of particles within a surrounding bat…

cs.CV2023

Food-500 Cap: A Fine-Grained Food Caption Benchmark for Evaluating Vision-Language Models

Zheng Ma, Mianzhi Pan, Wenhan Wu +4

Vision-language models (VLMs) have shown impressive performance in substantial downstream multi-modal tasks. However, only comparing the fine-tuned performance on downstream tasks…