Error-free Training for MedMNIST Datasets

EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence

arXiv:2604.23325v1 Announce Type: cross Abstract: Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressions. Current

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

arXiv:2604.23466v1 Announce Type: cross Abstract: NVIDIA’s CUDA Tile (CuTile) introduces a Python-based, tile-centric abstraction for GPU kernel development that aims to simplify programming while retaining

Mixture of Heterogeneous Grouped Experts for Language Modeling

arXiv:2604.23108v1 Announce Type: cross Abstract: Large Language Models (LLMs) based on Mixture-of-Experts (MoE) are pivotal in industrial applications for their ability to scale performance efficiently.

Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption

arXiv:2604.23245v1 Announce Type: cross Abstract: The use of Machine Learning (ML) for data-driven decision-making often relies on access to sensitive datasets, which introduces privacy challenges.

Institutions for the Post-Scarcity of Judgment

arXiv:2604.22966v1 Announce Type: cross Abstract: Each major technological revolution inverts a particular scarcity and rebuilds institutions around the shift. The near-consensus diagnosis of the AI

EAD-Net: Emotion-Aware Talking Head Generation with Spatial Refinement and Temporal Coherence

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Mixture of Heterogeneous Grouped Experts for Language Modeling

Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption

Institutions for the Post-Scarcity of Judgment

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