4 citations · 7 across the 14 of their papers we have counts for
15 papers
SPARE: Shared Perception and Adaptive Retrieval of Evidence for Streaming Video Understanding
Senbin Xu, Zijun Zhang, Xinhua Wu +7
Streaming video understanding requires answering questions from the observed video, with evidence drawn from recent observations or earlier events. Historical context can improve r…
From Semantic to Token Communication: The Next Paradigm for Large-Model-Driven 6G Intelligent Connectivity
Yu Ma, Zhen Gao, Li Qiao +11
The ambitious requirements of sixth-generation (6G) networks are driving communication systems from reliable bit delivery toward meaning-aware and task-oriented connectivity. Large…
Ada-TokenCom: Rate-Adaptive Token Communications via Large-Model-Driven Token Compression and Generation
Zijun Zhang, Li Qiao, Mahdi Boloursaz Mashhadi +3
Token Communications (TokenCom) has recently emerged as a new paradigm in which tokens serve as unified units for communication and computation, enabling efficient multimodal seman…
AirTF: Over-the-Air Token Fusion for Task-Oriented Multi-Modal Token Communications
Bole Liu, Li Qiao, Minghui Wu +2
In the Internet of Vehicles (IoV), transmitting high-dimensional multi-modal sensory data to edge servers for time-sensitive tasks faces severe spectrum bottlenecks. To address thi…
Knowledge Distillation Driven Semantic NOMA with GAN Refinement for 6G Robotic Vehicle Networks
Qifei Wang, Zhen Gao, Li Qiao +4
To achieve sustainable intelligent mobility, 6G-empowered robotic vehicles (RVs) require high-fidelity visual perception under stringent bandwidth and energy constraints. Semantic…
LGVSC: A Large-Model-Driven Generative Video Semantic Communication Framework
Yu Ma, Hang Yin, Li Qiao +4
Driven by the massive video transmission requirements in the Internet of Everything, semantic communication holds great promise for striking a balance between transmission efficien…
ToDMA: Large Model-Driven Massive Token Communications for Semantic Multiple Access
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +2
Token communications (TokenCom) is an emerging generative semantic communication paradigm, where tokens serve as compact representation units across modalities. Their contextual de…
Generative Video Semantic Communication via Multimodal Semantic Fusion with Large Model
Hang Yin, Li Qiao, Yu Ma +4
Despite significant advancements in traditional syntactic communications based on Shannon's theory, these methods struggle to meet the requirements of 6G immersive communications,…
Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +3
In this paper, we introduce token communications (TokCom), a large model-driven framework to leverage cross-modal context information in generative semantic communications (GenSC).…
Token-Domain Multiple Access: Exploiting Semantic Orthogonality for Collision Mitigation
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +1
Token communications is an emerging generative semantic communication concept that reduces transmission rates by using context and transformer-based token processing, with tokens s…
Unauthorized UAV Countermeasure for Low-Altitude Economy: Joint Communications and Jamming based on MIMO Cellular Systems
Zhuoran Li, Zhen Gao, Kuiyu Wang +5
To ensure the thriving development of low-altitude economy, countering unauthorized unmanned aerial vehicles (UAVs) is an essential task. The existing widely deployed base stations…
Generative Semantic Communication via Textual Prompts: Latency Performance Tradeoffs
Mengmeng Ren, Li Qiao, Long Yang +6
This paper develops an edge-device collaborative Generative Semantic Communications (Gen SemCom) framework leveraging pre-trained Multi-modal/Vision Language Models (M/VLMs) for ul…
CSI-GPT: Integrating Generative Pre-Trained Transformer with Federated-Tuning to Acquire Downlink Massive MIMO Channels
Ye Zeng, Li Qiao, Zhen Gao +5
In massive multiple-input multiple-output (MIMO) systems, how to reliably acquire downlink channel state information (CSI) with low overhead is challenging. In this work, by integr…
Massive Digital Over-the-Air Computation for Communication-Efficient Federated Edge Learning
Li Qiao, Zhen Gao, Mahdi Boloursaz Mashhadi +1
Over-the-air computation (AirComp) is a promising technology converging communication and computation over wireless networks, which can be particularly effective in model training,…
Latency-Aware Generative Semantic Communications with Pre-Trained Diffusion Models
Li Qiao, Mahdi Boloursaz Mashhadi, Zhen Gao +3
Generative foundation AI models have recently shown great success in synthesizing natural signals with high perceptual quality using only textual prompts and conditioning signals t…