Positional encoding has become the de facto standard for grounding deep neural networks on discrete point-wise positions, and it has achieved remarkable success in tasks where the input can be ...
Abstract: Generator-based adversarial attack methods aim to fool deep neural networks (DNNs) by training a generator for crafting adversarial examples (AEs). However, as DNNs evolve from Convolutional ...
Long-chain reasoning is one of the most compute-intensive tasks in modern large language models. When a model like DeepSeek-R1 or Qwen3 works through a complex math problem, it can generate tens of ...
Our long-term goal is to build efficient and reliable 2.5B diffusion-based decoding for document OCR. MinerU-Diffusion reframes document OCR as an inverse rendering problem and replaces slow, ...
Training of MinerU-Diffusion. Left: the target token sequence is randomly masked to form a partially observed input, and the model predicts only the masked positions under visual and prompt ...
FORT MYERS, Fla. — The Minnesota Twins’ position player group appears to be set. On Sunday, the Twins optioned Alan Roden to Triple-A and on Monday, they followed that by sending infielders Ryan ...
Abstract: Positional encoding is crucial for the Transformer to effectively process multimodal feature information in multispectral object detection. However, existing studies often directly apply ...
Anticipating short-term affective instability in bipolar disorder represents a longstanding challenge in computational psychiatry. Early signalling of transitions from stable to depressive, manic, or ...