A team of Google researchers introduced the Streaming Dense Video Captioning model to address the challenge of dense video captioning, which involves localizing events temporally in a video and generating captions for them. Existing models for video understanding...

In recent years, there has been a significant surge in the adoption of pre-trained language models, leading to an increase in the use of neural-based retrieval models. One such technique that has gained popularity for its effectiveness is Dense Retrieval (DR), which...

The proficiency of large language models (LLMs) in deciphering the complexities of human language has been a subject of considerable acclaim. Yet, when it comes to mathematical reasoning—a skill that intertwines logic with numerical understanding—these models often...

King’s College London researchers have highlighted the importance of developing a theoretical understanding of why transformer architectures, such as those used in models like ChatGPT, have succeeded in natural language processing tasks. Despite their widespread...

State-of-the-art language models require vast amounts of text data for pretraining, often in the order of trillions of words, which poses a challenge for smaller languages needing more extensive resources. While leveraging multilingual data is a logical solution, it’s...

In the field of machine learning, aligning language models (LMs) to interact appropriately with multimodal data like videos has been a persistent challenge. The crux of the issue lies in developing a robust reward system that can distinguish preferred responses from...