Unequal Error Protection

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8 papers2 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Beyond Token Accuracy: Prioritizing What Matters for Visual Reconstruction
Oct 2, 2026Zhicheng Liu, Zhouxiang Zhao, Chenliang Wu +2Unequal Error Protection Image Reconstruction
Zhejiang University
Semantic-Aware Neural Video Codec for Error-Resilient Low-Latency Transmission
Sep 14, 2026Matin Mortaheb, Homa Esfahanizadeh, Jinfeng Du +1Unequal Error Protection Semantic Communication
Nokia Bell Labs, Murray Hill, NJ 07974, USA
Polar Code Based Federated Learning: Convergence Analysis and Resource Allocation
Aug 14, 2026Han Xiao, Wei Kang, Nan LiuUnequal Error Protection Federated Learning
School of Information Science and Engineering, Southeast University, Nanjing 211189, China · National Mobile Communications Research Laboratory, Southeast University, Nanjing 211189, China
From Bit-Position Sensitivity to Unequal Error Protection for DNN Inference Memory
Jul 21, 2026Muhammad Husnain Mubarik, Karthik Mohan Kumar, Pedro Antonio Pena +2AI Accelerator Inference Unequal Error Protection
Advanced Micro Devices, Inc., USA
TWIST: Closed-Loop token Synchronization for Application-Aware Wireless Digital Twins
May 26, 2026Sige Liu, Kezhi WangUnequal Error Protection Semantic Communication
Department of Computer Science, Brunel University London, Uxbridge UB8 3PH, U.K.
TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems
May 20, 2026Sige Liu, Kezhi WangUnequal Error Protection Semantic Communication
Department of Computer Science, Brunel University London, Uxbridge UB8 3PH, U.K.
Rateless DeepJSCC for Broadcast Channels: a Rate-Distortion-Complexity Tradeoff
Mar 23, 2026Zijun Qin, Jingxuan Huang, Zesong Fei +3Joint Source-Channel Coding Unequal Error Protection
Department of Electrical and Computer Engineering, University of Hong Kong, Pok Fu Lam, Hong Kong S.A.R., China · School of Information and Electronics, Beijing Institute of Technology, Beijing, China · School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China
Video TokenCom: Textual Intent-Guided Multi-Rate Video Token Communications with UEP-Based Adaptive Source-Channel Coding
Mar 2, 2026Jingxuan Men, Mahdi Boloursaz Mashhadi, Ning Wang +3Unequal Error Protection Semantic Communication
5GIC & 6GIC, Institute for Communication Systems (ICS), University of Surrey, U.K. · Smart Internet Lab, University of Bristol, U.K. · British Telecom Research Lab, BT Group plc, U.K.

Oct 2, 2026J/K move · Enter open · S save

Beyond Token Accuracy: Prioritizing What Matters for Visual Reconstruction

Zhicheng Liu, Zhouxiang Zhao, Chenliang Wu, Zhaohui Yang+1

Zhejiang University

Unequal Error Protection Image Reconstruction Wireless Resource Allocation Visual Token Compression

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Tokens have become a unified interface for multimodal foundation models, making visual-token communication a natural paradigm for efficient image delivery. However, existing methods typically rely on static policies that cannot jointly adapt to image content and channel conditions. Moreover, their token-level utility objectives do not necessarily translate into improved image reconstruction quality. In this paper, we propose AdapToC, an adaptive, reconstruction-oriented visual-token communication framework. At the transmitter, an adaptive selector jointly models image content, channel state, and communication budget to perform instance-wise resource allocation. Rather than using a fixed token rate and protection policy, it dynamically determines how many tokens should be transmitted and assigns different protection levels according to token importance and current channel conditions. At the receiver, an adaptive MaskGIT receiver incorporates channel reliability into contextual token modeling. It distinguishes tokens with different reliability levels, preserves high-confidence observations, corrects potentially corrupted tokens, and iteratively reconstructs missing content from the received evidence and global visual context. By co-designing token quantity, unequal protection, and reliability-aware recovery for image-level reconstruction quality, AdapToC achieves a peak mean PSNR gain of 4.20 dB over the strongest static baseline under matched communication costs and state-of-the-art performance among the evaluated visual-token communication methods.