Large vision-language models often generate content that isn't supported by the input image. To prevent this 'hallucination', researchers propose a me...
Researchers propose DA-WAM, a framework that combines predictive representation learning and decision-making for safe autonomous driving. DA-WAM aims ...
Researchers have proposed a method called DistScan to detect backdoors in object detection models. A backdoor is a hidden trigger that causes the mode...
Researchers have developed a new framework called Open-MOPD to address the issue of capability imbalance in multi-teacher on-policy distillation. This...
Researchers have proposed a new method for imputing missing values in time series data. The Masked Diffusion Time-series Imputation Model (MDTIM) uses...
Researchers have developed a new AI framework called PGFS++, which can improve the properties of molecules in early-stage drug discovery. The framewor...
Researchers have developed an experimental framework for communicating with entities that categorize reality differently from humans. They created two...
Researchers have found a way to interpret the predictions made by gradient-boosted ensembles, which are often used in machine learning. By viewing eac...
Researchers have developed a method to distribute large language models across multiple Intel AI PCs, allowing for faster and more efficient inference...
Researchers have developed a deep learning model that can predict seasonal precipitation anomalies in central China. The model translates atmospheric ...
Researchers from a team of authors have published a paper describing their winning submission to the AES AIMLA 2025 Challenge. They investigated two f...
Researchers have developed a new approach to training AI models for long-context reasoning tasks. They found that traditional on-policy distillation m...