Towards a lingua franca for knowledge graph question answering systems Machine Translation (MT) can enhance existing Question Answering (QA) systems, which have limited language capabilities, by enabling them to support multiple languages. However, there is one major drawback of MT — often, it fails at translating named entities that are not translatable word-by-word. For example,…
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ChatGPT and similar tools based on large language models (LLMs) are amazing. But they aren’t all-purpose tools.
It’s just like choosing other tools for building and creating. You need to pick the right one for the job. You wouldn’t try to tighten a bolt with a hammer or flip a hamburger patty…
In the past year, large vision language models (LVLMs) have become a prominent focus in artificial intelligence research. When prompted differently, these models show promising performance across various downstream tasks. However, there’s still significant potential for improvement in LVLMs’ image perception capabilities.
Enhanced perceptual abilities for visual concepts are crucial for advancing model development and…
Exploring mental well-being insights with zero-shot classification Artwork by Vivian Peng — reposted with permissionSentiment analysis is a powerful tool in natural language processing (NLP) for exploring public opinions and emotions in text. In the context of mental health, it can provide compelling insights into the holistic wellness of individuals. As a summer data science…
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SQL, or Standard Query Language, is a programming language for managing and manipulating data within a relational database management system (RDBMS). It’s a standard language used in many companies to help businesses access data smoothly. Because it’s widely used, the employment usually cites SQL as one of the necessary skills.…
Artificial Intelligence (AI), particularly through deep learning, has revolutionized many fields, including machine translation, natural language understanding, and computer vision. The field of medical imaging, specifically chest X-ray (CXR) interpretation, is no exception. CXRs, the most frequently performed diagnostic imaging tests, hold immense clinical significance. The advent of vision-language foundation models (FMs) has opened new…
A deep dive on a powerful and popular algorithm Photo by FlyD on UnsplashFrom drug discovery to species classification, credit scoring to cybersecurity and more, the random forest is a popular and powerful algorithm for modeling our complex world. Its versatility and predictive prowess would seem to require cutting-edge complexity, but if we dig into…
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There’s one single lesson I learned from using ChatGPT. It’s wonderfully helpful in data science, but you must scrutinize everything it outputs. It’s great for some tasks and can do them very quickly and accurately. For some other tasks, it’s good enough, and you’ll have to prompt it several times.…
A team of researchers associated with Peking University, Pika, and Stanford University has introduced RPG (Recaption, Plan, and Generate). The proposed RPG framework is the new state-of-the-art in the context of text-to-image conversion, especially in handling complex text prompts involving multiple objects with various attributes and relationships. The existing models which have shown exceptional results…
The rise of the MoEs Image by the author — Generated with DALL-ESince the release of Mixtral-8x7B by Mistral AI, there has been a renewed interest in the mixture of expert (MoE) models. This architecture exploits expert sub-networks among which only some of them are selected and activated by a router network during inference. MoEs…