NVIDIA showcases Neural Texture Compression at GTC 2026, cutting VRAM usage by up to 85% with real-time AI reconstruction.

Abstract: Positional encoding is crucial for the Transformer to effectively process multimodal feature information in multispectral object detection. However, existing studies often directly apply ...

Comorbidity—the co-occurrence of multiple diseases in a patient—complicates diagnosis, treatment, and prognosis. Understanding how diseases connect at a molecular level is crucial, especially in aging ...

Neural Radiance Fields (NeRF) have revolutionized novel view synthesis through volumetric scene representations, where positional encoding plays a critical role in high-frequency detail capture.

Spring training is a largely meaningless set of exhibitions to some veteran players but the land of opportunity to others, particularly young prospects looking to break through to the big leagues.

Summary: Researchers showed that large language models use a small, specialized subset of parameters to perform Theory-of-Mind reasoning, despite activating their full network for every task. This ...

Instead of using RoPE’s low-dimensional limited rotations or ALiBi’s 1D linear bias, FEG builds position encoding on a higher-dimensional geometric structure. The idea is simple at a high level: Treat ...

It seems step1xedit is adapted from Flux, with connector and Qwen integrated. Is the DiT backbone trained from scratch, or finetuned from a pretrained Flux model (e.g., flux-1.dev)? If finetuned from ...