Beyond Token Accuracy: Prioritizing What Matters for Visual Reconstruction
cs.CV
Submitted: 2026-10-02
Updated: 2026-10-02
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- DeepJSCC-l++: Robust and Bandwidth-Adaptive Wireless Image Transmission
- Joint Coding-Modulation for Digital Semantic Communications via Variational Autoencoder
- Chameleon: Mixed-Modal Early-Fusion Foundation Models
- Muse: Text-To-Image Generation via Masked Generative Transformers
- Nonlinear Transform Source-Channel Coding for Semantic Communications
- Generative Joint Source-Channel Coding for Semantic Image Transmission
- Taming Transformers for High-Resolution Image Synthesis
- Improved Masked Image Generation with Token-Critic
- MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis
- TONIC: Token-Centric Semantic Communication for Task-Oriented Wireless Systems
- Token Communications: A Large Model-Driven Framework for Cross-modal Context-aware Semantic Communications
- Zero-Shot Text-to-Image Generation
- Generating Diverse High-Fidelity Images with VQ-VAE-2
- Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
- DeepJSCC-Q: Constellation Constrained Deep Joint Source-Channel Coding
- Neural Discrete Representation Learning
- DiffCom: Channel Received Signal is a Natural Condition to Guide Diffusion Posterior Sampling
- Emu3: Next-Token Prediction is All You Need
- Deep Joint Source-Channel Coding for Adaptive Image Transmission over MIMO Channels
- Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation
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