Transformers have become the backbone of deep learning models for tasks that require sequential data processing, such as natural language ...
Speech synthesis has become a transformative area of research, focusing on creating natural, synchronized audio outputs from various inputs. Integrating ...
The current design of causal language models, such as GPTs, are inherently fraught with the challenge of semantic coherence over ...
Transformers have transformed artificial intelligence, delivering unmatched performance in NLP, computer vision, and multimodal data integration. These models excel at ...
The rise of Transformer-based models has significantly advanced the field of natural language processing. However, training these models is often ...
Current challenges in text-to-speech (TTS) systems revolve around the inherent limitations of autoregressive models and their complexity in accurately aligning ...
Traffic forecasting is a fundamental aspect of smart city management, essential for improving transportation planning and resource allocation. With the ...
Minish Lab was recently introduced Model2Veca revolutionary tool designed to distill smaller and faster models from any Sentence Transformer. With ...
A gentle introduction to the latest model of multimodal transfusionRecently, Meta and Waymo published their latest paper:Transfusion: Predicting the next ...
This paper presents Show-o, a unified transformer model that integrates multimodal understanding and generation capabilities within a single architecture. As ...
