XDA Developers on MSN

I tested Gemma 4, Qwen 3.5, and Ministral 3 for vision tasks, and only one understood the assignment

One of these read the picture, the other two guessed ...
Frontiers

Deep learning-driven 3D marine nitrate estimation: uncertainty mitigation through underwater signal exploitation and label augmentation

Nitrate is a critical limiting nutrient that significantly influences marine primary productivity and carbon sequestration. However, three-dimensional observation and reconstruction of oceanic nitrate ...
Europe PMC

Enhanced IoMT security framework using group teaching optimized auto-encoder for intrusion detection.

Providing security to Internet of Medical Things (IoMT) is significant worldwide problem for future generations its implementation to be successful. The traditional security methodologies developed ...
IEEE

Learning Defendant-aware Label Representation for Multi-Defendant Charge Prediction

Abstract: Automatic charge prediction based on deep learning methods is a crucial task in legal judgment prediction, aiming to predict the charges based on the fact description for a criminal case.
GitHub

CLIP inference in plain C/C++ with no extra dependencies

This is a dependency free implementation of well known CLIP by OpenAI, thanks to the great work in GGML. You can use it to work with CLIP models from both OpenAI and LAION in Transformers format. clip ...
Frontiers

Uncertainty is not sufficient for identifying noisy labels in training data for binary segmentation of building footprints

Obtaining high quality labels is a major challenge for the application of deep neural networks in the remote sensing domain. A common way of acquiring labels is the usage of crowd sourcing which can ...
acm.org

Language Models: Past, Present, and Future

Natural language processing (NLP) has undergone revolutionary changes in recent years. Thanks to the development and use of pre-trained language models, remarkable achievements have been made in many ...
Visual Studio Magazine

Autoencoder Anomaly Detection Using PyTorch

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...