Modern digital writing assistants are intelligent agents that leverage AI technologies to help users write high-quality texts. Existing AI writing assistants however typically provide only limited functions such as spelling and grammatical error checking and basic rewriting for clarity and brevity. In the new paper Effidit: Your AI Writing Assistant…

The task of simultaneously classifying, segmenting, and tracking multiple object instances in videos is referred to as video instance segmentation (VIS). Modern VIS transformers (VisTR) use a per-clip approach and have shown impressive end-to-end performance but suffer from long training times and high computation costs due to their frame-wise dense…

Text games have emerged as a fundamental research paradigm for learning and evaluating embodied agents on natural language processing (NLP) tasks. …

Today’s transformer-based large language models (LLMs) have proven a game-changer in natural language processing, achieving state-of-the-art performance on reading comprehension, question answering and common sense reasoning benchmarks. …

Introduced in the award-winning 2020 ECCV paperNeRF: Representing Scenes as Neural Radiance Fields for View Synthesis, Neural Radiance Fields (NeRFs) leverage a fully connected (non-convolutional) deep neural network to synthesize novel views of complex 3D scenes based on partial 2D views. Although NeRFs have achieved state-of-the-art performance in generating photo-realistic…

The deblurring of fast-moving objects is a longstanding challenge in photography and image processing. Although we have witnessed rapid progress in general image deblurring, most approaches require computational power beyond that of mobile phones and are unable to process high-resolution images with local motion. In the new paper Face Deblurring…

The ongoing deployment of deep neural networks in the field of natural language processing (NLP) has enabled much more efficient AI agents for a variety of practical applications in customer service, etc. But sometimes people — for example, seniors or those experiencing social isolation — would just like to enjoy…

State-of-the-art AI models have ballooned to billions of parameters in recent years. Although the machine learning (ML) community has shown keen interest in the scaling properties of transformer-based models, there has been relatively little research on scaling effects with regard to the inductive biases imposed by different model architectures. In…

Gradient boosting decision trees (GBDT) is a powerful machine learning algorithm widely used in real-life applications such as online advertising, search ranking, time-series prediction, etc. …