output
20152026
most citedContextformer: A Transformer with Spatio-Channel Attention for Context Modeling in Learned Image Compression

83 citations

54 papers

cs.LG2026

Greening AI Inference with Accuracy and Latency-aware User Incentives

Vasilios A. Siris, Adamantia Stamou, George D. Stamoulis +2

The widespread use of AI services has raised concerns for its environmental sustainability, towards which recent studies have identified carbon emissions of AI inference as the maj…

cs.CR2025

TICAL: Trusted and Integrity-protected Compilation of AppLications

Robert Krahn, Nikson Kanti Paul, Franz Gregor +4

During the past few years, we have witnessed various efforts to provide confidentiality and integrity for applications running in untrusted environments such as public clouds. In m…

cs.IT2025★ 1 cited

Rate-Adaptive Protograph-Based MacKay-Neal Codes

Ayman Zahr, Emna Ben Yacoub, Balázs Matuz +1

Rate-adaptive MacKay-Neal (MN) codes based on protographs are analyzed. The code construction employs an outer distribution matcher (DM) to adapt the rate of the scheme. The DM is…

cs.NI2025★ 2 cited

PRATA: A Framework to Enable Predictive QoS in Vehicular Networks via Artificial Intelligence

Federico Mason, Tommaso Zugno, Matteo Drago +3

Predictive Quality of Service (PQoS) makes it possible to anticipate QoS changes, e.g., in wireless networks, and trigger appropriate countermeasures to avoid performance degradati…

eess.IV2025★ 1 cited

Overview of Variable Rate Coding in JPEG AI

Panqi Jia, Fabian Brand, Dequan Yu +3

Empirical evidence has demonstrated that learning-based image compression can outperform classical compression frameworks. This has led to the ongoing standardization of learned-ba…

cs.CV2025★ 3 cited

ConsistentDreamer: View-Consistent Meshes Through Balanced Multi-View Gaussian Optimization

Onat Şahin, Mohammad Altillawi, George Eskandar +2

Recent advances in diffusion models have significantly improved 3D generation, enabling the use of assets generated from an image for embodied AI simulations. However, the one-to-m…