Most modern visualization authoring tools like Charticulator, Data Illustrator, and Lyra, and libraries like ggplot2, and VegaLite expect tidy data, where every variable to be visualized is a column ...

Edge devices like smartphones, IoT gadgets, and embedded systems process data locally, improving privacy, reducing latency, and enhancing responsiveness, and AI is getting integrated into these ...

Artificial Intelligence is increasingly integrated into various sectors, yet there is limited empirical evidence on its real-world application across industries. Traditional research methods—such as ...

Test-Time Scaling (TTS) is a crucial technique for enhancing the performance of LLMs by leveraging additional computational resources during inference. Despite its potential, there has been little ...

Artificial intelligence models face a fundamental challenge in efficiently scaling their reasoning capabilities at test time. While increasing model size often leads to performance gains, it also ...

Reasoning tasks are yet a big challenge for most of the language models. Instilling a reasoning aptitude in models, particularly for programming and mathematical applications that require solid ...

Multi-agent AI systems utilizing LLMs are increasingly adept at tackling complex tasks across various domains. These systems comprise specialized agents that collaborate, leveraging their unique ...

Artificial intelligence has made significant strides, yet developing models capable of nuanced reasoning remains a challenge. Many existing models struggle with complex problem-solving tasks, ...

Human-robot collaboration focuses on developing intelligent systems working alongside humans in dynamic environments. Researchers aim to build robots capable of understanding and executing natural ...

Mathematical reasoning remains one of the most complex challenges in AI. While AI has advanced in NLP and pattern recognition, its ability to solve complex mathematical problems with human-like logic ...

Competitive programming has long served as a benchmark for assessing problem-solving and coding skills. These challenges require advanced computational thinking, efficient algorithms, and precise ...

Yann LeCun, Chief AI Scientist at Meta and one of the pioneers of modern AI, recently argued that autoregressive Large Language Models (LLMs) are fundamentally flawed. According to him, the ...